LMU BioDB 2024 - User contributions [en]

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2026-07-21T20:49:08Z

Kdahlquist: delete extraneous template

==Overview==

This protocol describes all the steps necessary to perform aRNA synthesis, labeling, hybridization, and scanning of DNA microarrays for ''Saccharomyces cerevisiae'', beginning with total RNA.

==Materials==

===Supplies===
'''NOTE: RNase-free supplies should be used whenever possible.'''

* SealRite 1.5 mL Natural Microcentrifuge Tubes (free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1615-5500)
* TipOne 101-1000 μL Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1126-7810)
* TipOne 1-200 μL Graduated Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1120-8810)
* TipOne 0.1-10 μL Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1121-3810)
* 50 ml conical screw cap tubes, copolymer, bulk, sterile (USA Scientific Catalog <nowiki>#</nowiki>1500-1211)
* Powder-free latex exam gloves (USA Scientific Catalog <nowiki>#</nowiki>4900-2200, 4900-3300, 4900-4400)
* multiwipes, small and large (Denville Scientific Catalog <nowiki>#</nowiki>C5709-1A, C5709-3A)
** a.k.a. Kim wipes
** Denville Scientific sells a generic version that is less expensive than the name brand
* aluminum foil (from grocery store or other such supplier)
* compressed air duster
** VWR sells something called the "Whoosh Duster" (VWR Catalog <nowiki>#</nowiki>16650-027), but I've found that one purchased from an electronics store (less expensive) works fine ([[User:Kam D. Dahlquist|Kam D. Dahlquist]] 20:46, 15 August 2008 (EDT))
* trUView™ Disposable Cuvettes (BioRad Catalog <nowiki>#</nowiki>1702510)
** UV-transparant microcuvettes hold 50 μL total volume
** can be cleaned and re-used indefinitely when you don't need to recover the sample from them
** you don't need these if you have access to an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] (or Thermo NanoDrop or GE Nanovue)
* RNaseZap (Denville Scientific Catalog <nowiki>#</nowiki>D1180)
** Actually an Applied Biosystems/Ambion product Catalog <nowiki>#</nowiki>AM9780, but it is less expensive if you buy it from Denville

===Reagents===
'''NOTE: RNAse-free reagents should be used whenever possible.'''

* Amino Allyl MessageAmp™ II aRNA Amplification Kit (Applied Biosystems Catalog <nowiki>#</nowiki>AM1753)
** 20 reactions per kit
** [https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd=catNavigate2&catID=603176 Applied Biosystems Catalog Web Page]. Originally an Ambion product. Ambion was acquired by Applied Biosystems which has now merged with Invitrogen and is called "Life Technologies" and the kit can only be purchased through them.
** [http://www.ambion.com/catalog/ABProdGrp.html?fkProdGrp=341 Ambion Product Web Page]. Contains useful links.
** [http://www.ambion.com/techlib/prot/fm_1753.pdf Ambion Protocol (PDF)]. Protocol packaged with kit.
* CyDye Post-Labeling Reactive Dye Pack (GE Healthcare Life Sciences Catalog <nowiki>#</nowiki>RPN5661)
** 12 X Cy3 + 12 X Cy5 per box
** [http://www1.gelifesciences.com/aptrix/upp01077.nsf/Content/Products?OpenDocument&parentid=25800563&moduleid=164924 GE Healthcare Product Web Page]. Distributed through [http://www.vwrsp.com/catalog/product/index.cgi?catalog_number=95040-134&inE=1&highlight=95040-134&reference_type=1&partnumber=RPN5661&sim_code=1.0 VWR].
** Use protocol for Amino Allyl MessageAmp™ II aRNA Amplification Kit.
* [[TE | TE Buffer]] (USB Catalog #75893)
* Nuclease-free water (non-DEPC treated)
** Nuclease-free water is provided in the Amino Allyl MessageAmp™ II aRNA Amplification Kit and is sufficient for the μL quantities called for throughout the protocol; additional water can be purchased from Applied Biosystems/Ambion, but it is expensive.
** DEPC is an oxidizer and should be fully removed from water used with DNA microarrays because the Cy5 dye is prone to degradation by oxidation.
** For larger quantities of nuclease-free water (non-DEPC treated) that are needed to dilute 20X SSC for washes, for example, I use Water, ASTM Type II, non-sterile, Reagent Grade, ACS (VWR Catalog <nowiki>#</nowiki>RC91505) that can be purchased in 10 L or 20 L cubes. This water was recommended by [http://www.genisphere.com Genisphere] in the DyeSaver 2 protocol as being validated for use with microarrays and not containing components that will oxidize Cy5; [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 20:24, 15 August 2008 (EDT))
* RNA Fragmentation Reagents (Applied Biosystems Catalog #AM8740)
** [http://www.ambion.com/techlib/spec/sp_8740.pdf Product information]
** 200 reactions per kit
* DIG Easy Hyb (Roche Applied Science Catalog #11796895001)
* Fish sperm DNA Solution 10 mg/mL
** Have used Ultra Pure Salmon Sperm DNA Solution from Invitrogen (Catalog #15632-011)
** When that runs out will use DNA, MB-grade from fish sperm from Roche Applied Science (Catalog #11467140001) which is significantly less expensive
* Oligo dA, 10-20mer, 1μg/mL (Invitrogen Catalog #POLYA.GF)
* 100% ethanol (Sigma Catalog #E702-3)
** for adding to wash buffers in Amino Allyl MessageAmp™ II aRNA Amplification Kit
* 20X [[SSC | SSC]] (USB Catalog #19629)
** for making post-hybridization wash buffers
* 20% SDS (USB Catalog #75832)
** for making post-hybridization wash buffers
* Hybri-slips (Sigma Catalog #H0784)
** pack of 100
** inexpensive, disposable, easy-to-use, made out of plastic
** L × W × thickness 60 mm × 24 mm × 0.25 mm
* Yeast 6.4K Array (Y6.4K) ([http://www.microarrays.ca/products/types.html#Y6.4K University Health Network Microarray Centre, Toronto])
** NOTE: they have discontinued printing these chips as of 7/31/10. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:38, 22 July 2010 (EDT)''

==== Slide Coating Solution ====
* "Home-brew" version of Genisphere DyeSaver 2
* 2% PEG (MW cut-off 2000) in 1:1 solution of acetone and toluene
* 200 mL needed to fill Coplin jar
* Weigh 4.0 g of polyethylene glycol (Mn ca. 2000) and transfer to a dry glass reagent bottle. Add 100 mL of HPLC grade acetone (water content less than 0.5%) and close the bottle with a lid. Swirl the bottle gently to dissolve the solid completely. When a clear solution is formed add 100 mL of anhydrous toluene and mix the solution before using in the coating experiments. Note: do not use any plastic in this procedure. Store at room temperature in a fume hood.
* Can be re-used (but not indefinitely)
* NOTE: PEG 8000 does '''NOT''' work in this recipe. It will not dissolve in the acetone. I have not tried MW cut-offs between 2000 and 8000, though. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:36, 22 July 2010 (EDT)''
* NOTE: PEG is hygroscopic, store aliquots in dessicator. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 18:53, 25 January 2011 (EST)''

===Equipment===
* Dedicated set of RNase-free pipetmen
* Speedvac
* Water bath set to 50°C
* Water bath set to 37°C
* Heat block set to 70°C
* Microcentrifuge
* Corning hybridization chambers
* racks (for 1.5 mL microcentrifuge tubes)
* racks (for 50 mL conical tubes)
* ice bucket and ice
* forceps
* slide box
* glass Coplin jar (to hold Slide Coating Solution)
* UV/vis spectrophotometer

==Procedure==
===General Notes===
* Use RNase-free reagents and supplies and maintain good RNase-free technique throughout.
* At the beginning of each day's work, clean the bench top and pipetman shafts with RNaseZap.
* Keep all samples on ice unless specifically noted otherwise.
* Once the Cy3 and Cy5 dye packages have been opened, all procedures must be carried out in the dark.
* Generally, we perform up to 10 reactions (5 slides) at one time.
* Make sure to perform multiple reactions for the reference sample so that there is enough aRNA for each of the chips.
* If using kit for the first time, add the appropriate amount of 100% ethanol to the Wash Buffer.

===Day 1===

'''''Note that Ambion/Applied Biosystems/Life Technologies revised the protocol for the AM1753 Amino Allyl MessageAmp II aRNA Amplification Kit and we started using the revised protocol on 12/9/10.'''''

# Dry 1 μg of yeast total RNA to less than 10 μL in a SpeedVac.
#* 1 μg is the largest amount recommended for the kit.
#* RNA can be dried ahead of time and stored at -80°C.
# '''Reverse Transcription to Synthesize First Strand of cDNA:''' follow steps C1-C3 in protocol.
#* Use 42°C water bath for step C4.
#* Thaw reagents and make Master Mix for step D1 and immediately proceed to step D1 when 2 hours are up.
# '''Second Strand cDNA synthesis:''' perform steps D1-D2.
#* Use 16°C water bath in the cold room for step D2.
#* Potential stopping point for Day 1. Freeze samples at -20°C. Protocol says it is better to go on to cDNA purification before freezing, though.
# '''cDNA Purification:''' Aliquot nuclease-free water needed for elution step (E4) plus some extra into a 1.5 mL microcentrifuge tube and pre-heat to 55°C in a water bath (the protocol says to heat the entire bottle, but this is unwieldy).
# Perform steps E1-E5.
# Stopping point for Day 1. Freeze samples at -20°C.

===Day 2===

# Perform steps F1-F3 '''(In Vitro Transcription to Synthesize Amino Allyl-Modified aRNA.)'''
#* Perform step F2 in 37°C water bath for six hours. The protocol says to incubate for 4-14 hours. However, it is important to incubate the same amount of time for each experiment to reduce variability.
#* Potential stopping point for Day 2. Freeze samples at -80°C.
# '''aRNA Purification:''' Aliquot nuclease-free water needed for elution step (G5) plus some extra into a 1.5 mL microcentrifuge tube and pre-heat to 50°C in a water bath.
# Perform steps G1-G5.
#* Do not vortex and do not centrifuge in steps G1 and G2 and proceed as quickly as possible to step G3, otherwise the aRNA will start precipitating and you will lose it.
#* We have also noticed a degradation in quality of the spin columns supplied by Ambion (now Invitrogen) in this kit. The filters do not stay seated in the column and the column material seems to come down into the elution tube. To remedy this, we have begun to spin the columns at half the speed and for twice as long a time as called for in the protocol. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:55, 22 July 2010 (EDT)''
# Stopping point for Day 2. Freeze samples at -80°C.

===Day 3===

'''Assess aRNA yield and quality''' through UV absorbance and agarose gel electrophoresis.

# Make a 1:50 dilution of each aRNA sample by diluting 2 μL of sample into 98 μL of TE Buffer.
#* Alternately, read 2 μL of sample directly on an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] using the 0.2 mm lid (factor 50).
# Read absorbance at 260 and 280 nm.
# Calculate the concentration of aRNA using the formula
A260 X dilution factor (50) X 40 μg/mL = concentration (μg/mL) (for 1 cm path length)
* The 260/280 ratio should be between 1.7 and 2.1.
* Calculate and aliquot the volume of aRNA required for 1 μg of aRNA into a fresh 1.5 mL microcentrifuge tube for each sample.
* This could be a stopping point for Day 3, storing the samples at -80°C, but ideally, go on to the next step:

'''Agarose gel electrophoresis using Reliant RNA Gel System by Lonza'''

# Bring volume of aRNA to 5 μL using nuclease-free water.
# Add 5 μL of 2X formaldehyde sample buffer (loading dye) (Lonza) to each sample.
#* Remove aliquotted sample of 0.2-10 kb RNA markers (USB) from -80°C freezer (dye already added) and include in subsequent steps.
# Incubate 65°C for 15 minutes.
# Incubate on ice for 1 minutes.
# In the meantime, place the pre-cast Reliant gel on the loading tray of the large horizontal gel box.
#* Make sure that it is not crooked.
# Fill box to cover gel with 1X AccuGENE MOPS Running Buffer (Lonza).
#* Dilute 100 mL 10X AccuGENE MOPS Running Buffer with 900 mL MilliQ water to make 1 L.
#* Can be saved and re-used several times (stored at room temperature) for this type of gel.
# Run at 60-65 volts constant voltage for 2 hours.
# Remove gel from casting tray and place in small tupperware container.
# Submerge gel, just to cover, with MilliQ water.
# Add 10 μL of 10,000X GelStar Nucleic Acid Gel Stain (Lonza).
# Gently agitate for 20-30 minutes.
# Detect the RNA using UV transillumination with Kodak Gel Logic 100 station.
#* Amplified aRNA should appear as a smear from 250 to 5000 nt. The average size of amino allyl aRNA should be approximately 1400 nt.
#* Mix together aRNA samples if multiple reactions were performed for the same total RNA sample and each passes quality control. Re-read absorbance values and re-calculate concentration.
# Calculate the volume required for 20 μg of aRNA and aliquot into a fresh 1.5 mL microcentrifuge for each sample (if you need multiple reference samples, make sure to aliquot enough to hybe all of your chips). Store all samples at -80°C. Stopping point for day 3.

=== Day 4 ===

'''Indirect Labeling by Dye-Coupling'''

NOTE: this protocol uses the Applied Biosystems (formerly Ambion) Amino Ally MessageAmp II aRNA Amplification kit and GE (formerly Amersham) CyDye single reaction dye pack of the activated Cy3 and Cy5 dyes. The following steps are performed in the dark and are taken from the Ambion protocol.

# Place 20 μg of amino allyl aRNA in a nuclease-free microfuge tube, and vacuum dry to completion on the low setting (takes 30-60 minutes, depending on volume). After 30 minutes, check every 5-10 minutes and remove sample as soon as it is dry; do not overdry.
# To tube containing dried aRNA, add 9 μL Coupling Buffer and mix well/flash spin.
# Resuspend each CyDye pack in 11 μL of DMSO [and keep in the dark at room temperature for up to 1 hour until ready to use it.] You will need one Cy3 and one Cy5 pack per microarray.
#* It is helpful to flash spin the dried dye before adding the DMSO to make sure it is at the bottom of the tube.
# To tube containing the aRNA:Coupling Buffer mixture, add 11 µL of dye to each tube, mix thoroughly and flash spin.
#* NOTE: Make sure you know which dye to add to which tube!
# Incubate at room temperature in dark for 30 minutes (Wrap the rack with foil and place the rack in a drawer).
# To quench the reaction, add 4.5 μL of 4 M hydroxylamine and mix well. Incubate at room temperature in the dark for 15 minutes.
# Add 5.5 μL of nuclease-free water to bring each sample to 30 μL.

'''Removing Uncoupled Dye Material'''

# Before beginning the procedure, pipet enough nuclease-free water into a fresh tube so that you have 30 μL X number of tubes, plus a little extra. Pre-heat to 55°C. The water should heat for at least 10 minutes.
# Add 105 μL of aRNA Binding Buffer to each labeled aRNA sample--proceed to the next step immediately.
# Add 75 μL of 100% ethanol to each sample, and mix by pipetting the mixture up and down 3 times. '''''Do NOT vortex and do NOT centrifuge.'''''
# Place aRNA filter cartridges into the appropriate number of collection tubes and pipet each sample from the previous step onto the appropriate column. Spin <s>1 minute at 10,000 X g</s> 2 minutes at 5,000 X g. Discard flow-through.
#* ''Note that we started having issues with the spin columns when Ambion/Applied Biosystems got purchased by Invitrogen and they started supplying Invitrogen columns in the kit. The resin would come down into the collection tube. We now spin for 2 minutes at 5,000 X g instead.''
# Apply 500 μL Wash Buffer to each filter cartridge. Spin 2 minutes at 5,000 X g. Discard flow-through.
# Spin again at 5,000 X g to remove trace amounts of Wash Buffer.
# Transfer filter cartridge into a fresh collection tube, being careful not to contaminate the new tube with any of the flow through from the previous step.
# To the center of the filter, add 15 μL of the nuclease-free water that you pre-heated to 55°C in step 1.
#* Note: the manufacturer's protocol calls for eluting twice with ''10 μL'' of the nuclease-free water, not 15 μL. However, we have observed that 5-8 μL of the total elution volume is retained on the column. By increasing the volumn slightly for each elution step we have increased our yield of labeled aRNA without diluting it too much. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:47, 22 July 2010 (EDT)''
# Let sit at room temperature for 2 minutes, then spin for 3 minutes at 5,000 X g.
# Repeat the elution with another 15 μL of nuclease-free water pre-heated to 50-60°C.
# Let sit at room temperature for 2 minutes, then spin for 3 minutes at 5,000 X g.
# Carefully transfer eluate to a 1.5 mL microfuge tube with a lid and place on ice.

'''Determine the concentration of labeled aRNA'''

# Dilute the labeled aRNA 1:50 by placing 1 μL of labeled aRNA into 49 μL of TE Buffer in a fresh tube.
#Read A260 and A550 for Cy3 or A650 for Cy5. If A260 is below 0.1, adjust dilution and try again.
#* A calculator for RNA concentration and labeling efficiency can be found at: [http://www.b2b.invitrogen.com/site/us/en/home/support/Research-Tools/Base-Dye-Ratio-Calculator.html http://www.b2b.invitrogen.com/site/us/en/home/support/Research-Tools/Base-Dye-Ratio-Calculator.html]
#* Alternately, read 2 μL of sample directly on an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] using the 0.2 mm lid (factor 50). It will compute the labeling efficiency automatically for you.
#* If you had multiple tubes of reference sample, and they all look OK on the spec, mix them together and re-read them as a single mixed sample.
# Calculate the volume required for 5 μg of Cy3 and Cy5 labeled aRNA. Mix those volumes of the appropriate Cy3 and Cy5 labeled aRNA together.
#* NOTE: Be sure to mix the right samples together!

'''Preparation for hybridization'''

# Vacuum dry the labeled aRNA that will be used for hybridization in a speedvac until the volume reaches 1-9 μL. Do not overdry (Check every 5 minutes.)
# If necessary, bring the volume of the dried labeled aRNA to 9 μL with nuclease-free water.
# Add 1 μL of Ambion 10X Fragmentation Buffer to the labeled aRNA.
# Incubate at 70°C for 15 minutes.
# Add 1 μL of the Stop Solution and place on ice.
# Speedvac the fragmented aRNA until the volume is < 5 μL. This will take about 5 minutes. Do NOT overdry.
# Make the hybridization master mix as follows:
X1 X6
DIG Easy Hyb solution 100 μL 600 μL
1 μg/μL oligo dA 0.38 μL 2.28 μL
10 mg/mL sonicated salmon sperm DNA 5 μL 30 μL
# Mix and flash spin. Incubate at 65°C for 2 minutes. Let cool until room temperature.
# Add 85 μL of the hybridization master mix to the paired, dried sample. Incubate at 65°C for 2 minutes. Flash spin and let cool until room temperature.
# Place the cover slip with the smooth side up on a support (a rack for 15 mL test tubes works great). Have the microarray slide ready with the hybridization chamber. Pipet the hybridization solution in a line on the cover slip, avoiding the introduction of air bubbles. Holding the microarray slide only by the edges (do not touch the front or back of the slide), pick up the cover slip with the DNA side of the slide down (the label side is the DNA side) and quickly invert the slide and place in the chamber with the DNA side and cover slip up.
# Pipet 11 μL of nuclease-free water into the wells in the hybridization chamber on either side of the slide. Place the cover on the chamber and lock the clips in place.
# Working quickly and keeping the hybridization chamber horizontal, place the chamber at the bottom of the 37°C water bath. Incubate for 15-16 hours.

=== Day 5 ===

'''Post-hybridization washing and scanning'''

# Remove the hybridization chamber from the water bath and dry the outside with a large kim wipe. Pull the clamps off and wipe again before opening the chamber. Lift the slide from the barcode end using forceps. Remove the coverslip by quickly, but gently dipping the slide in a 50 mL conical tube filled with room temperature 1X SSC. Let the coverslip slide off gently; hold the slide at the barcode end with forceps. Once the cover slip comes off, transfer the slide to another conical tube filled with 50°C 1X SSC/0.1% SDS. Incubate for 15 minutes in the 50°C waterbath.
# Transfer slide quickly to a second tube filled with 50°C 1X SSC/0.1% SDS. Do not let the slide dry out while transferring. Incubate for 15 minutes in the 50°C waterbath.
# Transfer slide quickly to a third tube filled with 50°C 1X SSC/0.1% SDS. Do not let the slide dry out while transferring. Incubate for 15 minutes in the 50°C waterbath.
# After the three washes are complete, rinse the slide in a tube filled with room temperature 1X SSC by plunging up and down 4-6 times.
# Rinse the slide in a tube filled with room temperature 0.1X SSC by plunging up and down 4-6 times. When you pull the slide out the last time, pull it out very slowly so that water droplets do not form on the surface of the slide. Then carefully blot the edges of the slide dry on a folded kim wipe, being careful not to touch the front or back surface of the slide. Use the compressed air duster to blow off any water droplets that remain. You are not blowing the water dry, but chasing it to the edge of the slide so that it can be blotted by the kim wipe.
# Carry the dry slide in a slide box covered in foil to the fume hood in the Keck Lab. Dip the slide into the coplin jar filled with 2% PEG (2000) in 1:1 acetone:toluene. Be careful not to dip the label into the solvent. Work quickly. Allow the slide to dry for about 1 minute before putting it back in the box and bringing it back into the Dahlquist lab for scanning. Keep the slide in the dark until scanning.

'''Scanning with the Axon GenePix 4000B Scanner'''

# Make sure that the computer is OFF before turning on the scanner.
# Remove the dust cover and turn on the scanner using the switch on the black box in the back of the scanner.
# Turn on the computer and login to the username “scanner”. Ask Dr. Dahlquist for the password.
# Let the scanner warm up for 15 minutes before scanning.
# See the pictures on the cabinet above the scanner for how to insert the slide. Be gentle!
#* The DNA side of the chip should be down and the barcode should be facing towards the front of the instrument.
# Open the Hardware Settings window (click the icon on the right-hand side that looks like the scanner with a key hanging off of it.)
# Make sure that the pixel size is set to 10, lines to average is set to 2, and focus position is set to 0. Set the PMT Gain for the 635 wavelength to 650 and the PMT Gain for the 532 wavelength to 550. The Power should be at 100% for both.
# Perform a Preview Scan by clicking the icon with the double arrows (looks like a "fastforward" icon).
#* While it is scanning, click on the histogram tab to see the Count Ratio of red to green signal. It should be within 10% of 1.00 (0.90 to 1.10). You can adjust the PMT Gain settings in the Hardware Settings window to adjust this ratio. The histogram tab will show you the data for the area of the image that is selected in the main Image window, so if you change the settings, you need to zoom to the area in which that setting applies.
#* Allow the Preview Scan to complete, so that the instrument will read the barcode. If it does not register the bar code, double-click on the barcode area at the bottom of the screen to enter it manually.
# Perform a Data Scan by clicking on the single arrow (second icon down on the right-hand side of the window). It will take ~10 minutes to complete the scanning of the slide.
# Save the data by clicking on the floppy/folder icon on the right hand side and choosing "Save Images" from the menu that appears.
#* In the dialog box that appears, make sure that the images are being saved as "Single-image tiffs". Use the barcode and date as part of the file names. Create a folder for today's date (yyyymmdd) in the C:\MicroarrayData folder to save the files.
# When you are finished scanning, turn off the scanner so that we do not wear out the laser and replace the dust cover.
# Go to the [[Dahlquist:GenePix_Pro_Software_Protocol | GenePix Pro Software Protocol]] for gridding the image and generating the data.

Sandbox

2026-07-21T20:47:43Z

Kdahlquist: paste in DNA microarray protocol

https://openwetware.org/wiki/Dahlquist:DNA_Microarray_Protocol

{{Template:Dahlquist}}

==Overview==

This protocol describes all the steps necessary to perform aRNA synthesis, labeling, hybridization, and scanning of DNA microarrays for ''Saccharomyces cerevisiae'', beginning with total RNA.

==Materials==

===Supplies===
'''NOTE: RNase-free supplies should be used whenever possible.'''

* SealRite 1.5 mL Natural Microcentrifuge Tubes (free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1615-5500)
* TipOne 101-1000 μL Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1126-7810)
* TipOne 1-200 μL Graduated Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1120-8810)
* TipOne 0.1-10 μL Filter Tips (sterile, free of detectable RNase, DNase, DNA & pyrogens; USA Scientific Catalog <nowiki>#</nowiki>1121-3810)
* 50 ml conical screw cap tubes, copolymer, bulk, sterile (USA Scientific Catalog <nowiki>#</nowiki>1500-1211)
* Powder-free latex exam gloves (USA Scientific Catalog <nowiki>#</nowiki>4900-2200, 4900-3300, 4900-4400)
* multiwipes, small and large (Denville Scientific Catalog <nowiki>#</nowiki>C5709-1A, C5709-3A)
** a.k.a. Kim wipes
** Denville Scientific sells a generic version that is less expensive than the name brand
* aluminum foil (from grocery store or other such supplier)
* compressed air duster
** VWR sells something called the "Whoosh Duster" (VWR Catalog <nowiki>#</nowiki>16650-027), but I've found that one purchased from an electronics store (less expensive) works fine ([[User:Kam D. Dahlquist|Kam D. Dahlquist]] 20:46, 15 August 2008 (EDT))
* trUView™ Disposable Cuvettes (BioRad Catalog <nowiki>#</nowiki>1702510)
** UV-transparant microcuvettes hold 50 μL total volume
** can be cleaned and re-used indefinitely when you don't need to recover the sample from them
** you don't need these if you have access to an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] (or Thermo NanoDrop or GE Nanovue)
* RNaseZap (Denville Scientific Catalog <nowiki>#</nowiki>D1180)
** Actually an Applied Biosystems/Ambion product Catalog <nowiki>#</nowiki>AM9780, but it is less expensive if you buy it from Denville

===Reagents===
'''NOTE: RNAse-free reagents should be used whenever possible.'''

* Amino Allyl MessageAmp™ II aRNA Amplification Kit (Applied Biosystems Catalog <nowiki>#</nowiki>AM1753)
** 20 reactions per kit
** [https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd=catNavigate2&catID=603176 Applied Biosystems Catalog Web Page]. Originally an Ambion product. Ambion was acquired by Applied Biosystems which has now merged with Invitrogen and is called "Life Technologies" and the kit can only be purchased through them.
** [http://www.ambion.com/catalog/ABProdGrp.html?fkProdGrp=341 Ambion Product Web Page]. Contains useful links.
** [http://www.ambion.com/techlib/prot/fm_1753.pdf Ambion Protocol (PDF)]. Protocol packaged with kit.
* CyDye Post-Labeling Reactive Dye Pack (GE Healthcare Life Sciences Catalog <nowiki>#</nowiki>RPN5661)
** 12 X Cy3 + 12 X Cy5 per box
** [http://www1.gelifesciences.com/aptrix/upp01077.nsf/Content/Products?OpenDocument&parentid=25800563&moduleid=164924 GE Healthcare Product Web Page]. Distributed through [http://www.vwrsp.com/catalog/product/index.cgi?catalog_number=95040-134&inE=1&highlight=95040-134&reference_type=1&partnumber=RPN5661&sim_code=1.0 VWR].
** Use protocol for Amino Allyl MessageAmp™ II aRNA Amplification Kit.
* [[TE | TE Buffer]] (USB Catalog #75893)
* Nuclease-free water (non-DEPC treated)
** Nuclease-free water is provided in the Amino Allyl MessageAmp™ II aRNA Amplification Kit and is sufficient for the μL quantities called for throughout the protocol; additional water can be purchased from Applied Biosystems/Ambion, but it is expensive.
** DEPC is an oxidizer and should be fully removed from water used with DNA microarrays because the Cy5 dye is prone to degradation by oxidation.
** For larger quantities of nuclease-free water (non-DEPC treated) that are needed to dilute 20X SSC for washes, for example, I use Water, ASTM Type II, non-sterile, Reagent Grade, ACS (VWR Catalog <nowiki>#</nowiki>RC91505) that can be purchased in 10 L or 20 L cubes. This water was recommended by [http://www.genisphere.com Genisphere] in the DyeSaver 2 protocol as being validated for use with microarrays and not containing components that will oxidize Cy5; [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 20:24, 15 August 2008 (EDT))
* RNA Fragmentation Reagents (Applied Biosystems Catalog #AM8740)
** [http://www.ambion.com/techlib/spec/sp_8740.pdf Product information]
** 200 reactions per kit
* DIG Easy Hyb (Roche Applied Science Catalog #11796895001)
* Fish sperm DNA Solution 10 mg/mL
** Have used Ultra Pure Salmon Sperm DNA Solution from Invitrogen (Catalog #15632-011)
** When that runs out will use DNA, MB-grade from fish sperm from Roche Applied Science (Catalog #11467140001) which is significantly less expensive
* Oligo dA, 10-20mer, 1μg/mL (Invitrogen Catalog #POLYA.GF)
* 100% ethanol (Sigma Catalog #E702-3)
** for adding to wash buffers in Amino Allyl MessageAmp™ II aRNA Amplification Kit
* 20X [[SSC | SSC]] (USB Catalog #19629)
** for making post-hybridization wash buffers
* 20% SDS (USB Catalog #75832)
** for making post-hybridization wash buffers
* Hybri-slips (Sigma Catalog #H0784)
** pack of 100
** inexpensive, disposable, easy-to-use, made out of plastic
** L × W × thickness 60 mm × 24 mm × 0.25 mm
* Yeast 6.4K Array (Y6.4K) ([http://www.microarrays.ca/products/types.html#Y6.4K University Health Network Microarray Centre, Toronto])
** NOTE: they have discontinued printing these chips as of 7/31/10. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:38, 22 July 2010 (EDT)''

==== Slide Coating Solution ====
* "Home-brew" version of Genisphere DyeSaver 2
* 2% PEG (MW cut-off 2000) in 1:1 solution of acetone and toluene
* 200 mL needed to fill Coplin jar
* Weigh 4.0 g of polyethylene glycol (Mn ca. 2000) and transfer to a dry glass reagent bottle. Add 100 mL of HPLC grade acetone (water content less than 0.5%) and close the bottle with a lid. Swirl the bottle gently to dissolve the solid completely. When a clear solution is formed add 100 mL of anhydrous toluene and mix the solution before using in the coating experiments. Note: do not use any plastic in this procedure. Store at room temperature in a fume hood.
* Can be re-used (but not indefinitely)
* NOTE: PEG 8000 does '''NOT''' work in this recipe. It will not dissolve in the acetone. I have not tried MW cut-offs between 2000 and 8000, though. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:36, 22 July 2010 (EDT)''
* NOTE: PEG is hygroscopic, store aliquots in dessicator. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 18:53, 25 January 2011 (EST)''

===Equipment===
* Dedicated set of RNase-free pipetmen
* Speedvac
* Water bath set to 50°C
* Water bath set to 37°C
* Heat block set to 70°C
* Microcentrifuge
* Corning hybridization chambers
* racks (for 1.5 mL microcentrifuge tubes)
* racks (for 50 mL conical tubes)
* ice bucket and ice
* forceps
* slide box
* glass Coplin jar (to hold Slide Coating Solution)
* UV/vis spectrophotometer

==Procedure==
===General Notes===
* Use RNase-free reagents and supplies and maintain good RNase-free technique throughout.
* At the beginning of each day's work, clean the bench top and pipetman shafts with RNaseZap.
* Keep all samples on ice unless specifically noted otherwise.
* Once the Cy3 and Cy5 dye packages have been opened, all procedures must be carried out in the dark.
* Generally, we perform up to 10 reactions (5 slides) at one time.
* Make sure to perform multiple reactions for the reference sample so that there is enough aRNA for each of the chips.
* If using kit for the first time, add the appropriate amount of 100% ethanol to the Wash Buffer.

===Day 1===

'''''Note that Ambion/Applied Biosystems/Life Technologies revised the protocol for the AM1753 Amino Allyl MessageAmp II aRNA Amplification Kit and we started using the revised protocol on 12/9/10.'''''

# Dry 1 μg of yeast total RNA to less than 10 μL in a SpeedVac.
#* 1 μg is the largest amount recommended for the kit.
#* RNA can be dried ahead of time and stored at -80°C.
# '''Reverse Transcription to Synthesize First Strand of cDNA:''' follow steps C1-C3 in protocol.
#* Use 42°C water bath for step C4.
#* Thaw reagents and make Master Mix for step D1 and immediately proceed to step D1 when 2 hours are up.
# '''Second Strand cDNA synthesis:''' perform steps D1-D2.
#* Use 16°C water bath in the cold room for step D2.
#* Potential stopping point for Day 1. Freeze samples at -20°C. Protocol says it is better to go on to cDNA purification before freezing, though.
# '''cDNA Purification:''' Aliquot nuclease-free water needed for elution step (E4) plus some extra into a 1.5 mL microcentrifuge tube and pre-heat to 55°C in a water bath (the protocol says to heat the entire bottle, but this is unwieldy).
# Perform steps E1-E5.
# Stopping point for Day 1. Freeze samples at -20°C.

===Day 2===

# Perform steps F1-F3 '''(In Vitro Transcription to Synthesize Amino Allyl-Modified aRNA.)'''
#* Perform step F2 in 37°C water bath for six hours. The protocol says to incubate for 4-14 hours. However, it is important to incubate the same amount of time for each experiment to reduce variability.
#* Potential stopping point for Day 2. Freeze samples at -80°C.
# '''aRNA Purification:''' Aliquot nuclease-free water needed for elution step (G5) plus some extra into a 1.5 mL microcentrifuge tube and pre-heat to 50°C in a water bath.
# Perform steps G1-G5.
#* Do not vortex and do not centrifuge in steps G1 and G2 and proceed as quickly as possible to step G3, otherwise the aRNA will start precipitating and you will lose it.
#* We have also noticed a degradation in quality of the spin columns supplied by Ambion (now Invitrogen) in this kit. The filters do not stay seated in the column and the column material seems to come down into the elution tube. To remedy this, we have begun to spin the columns at half the speed and for twice as long a time as called for in the protocol. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:55, 22 July 2010 (EDT)''
# Stopping point for Day 2. Freeze samples at -80°C.

===Day 3===

'''Assess aRNA yield and quality''' through UV absorbance and agarose gel electrophoresis.

# Make a 1:50 dilution of each aRNA sample by diluting 2 μL of sample into 98 μL of TE Buffer.
#* Alternately, read 2 μL of sample directly on an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] using the 0.2 mm lid (factor 50).
# Read absorbance at 260 and 280 nm.
# Calculate the concentration of aRNA using the formula
A260 X dilution factor (50) X 40 μg/mL = concentration (μg/mL) (for 1 cm path length)
* The 260/280 ratio should be between 1.7 and 2.1.
* Calculate and aliquot the volume of aRNA required for 1 μg of aRNA into a fresh 1.5 mL microcentrifuge tube for each sample.
* This could be a stopping point for Day 3, storing the samples at -80°C, but ideally, go on to the next step:

'''Agarose gel electrophoresis using Reliant RNA Gel System by Lonza'''

# Bring volume of aRNA to 5 μL using nuclease-free water.
# Add 5 μL of 2X formaldehyde sample buffer (loading dye) (Lonza) to each sample.
#* Remove aliquotted sample of 0.2-10 kb RNA markers (USB) from -80°C freezer (dye already added) and include in subsequent steps.
# Incubate 65°C for 15 minutes.
# Incubate on ice for 1 minutes.
# In the meantime, place the pre-cast Reliant gel on the loading tray of the large horizontal gel box.
#* Make sure that it is not crooked.
# Fill box to cover gel with 1X AccuGENE MOPS Running Buffer (Lonza).
#* Dilute 100 mL 10X AccuGENE MOPS Running Buffer with 900 mL MilliQ water to make 1 L.
#* Can be saved and re-used several times (stored at room temperature) for this type of gel.
# Run at 60-65 volts constant voltage for 2 hours.
# Remove gel from casting tray and place in small tupperware container.
# Submerge gel, just to cover, with MilliQ water.
# Add 10 μL of 10,000X GelStar Nucleic Acid Gel Stain (Lonza).
# Gently agitate for 20-30 minutes.
# Detect the RNA using UV transillumination with Kodak Gel Logic 100 station.
#* Amplified aRNA should appear as a smear from 250 to 5000 nt. The average size of amino allyl aRNA should be approximately 1400 nt.
#* Mix together aRNA samples if multiple reactions were performed for the same total RNA sample and each passes quality control. Re-read absorbance values and re-calculate concentration.
# Calculate the volume required for 20 μg of aRNA and aliquot into a fresh 1.5 mL microcentrifuge for each sample (if you need multiple reference samples, make sure to aliquot enough to hybe all of your chips). Store all samples at -80°C. Stopping point for day 3.

=== Day 4 ===

'''Indirect Labeling by Dye-Coupling'''

NOTE: this protocol uses the Applied Biosystems (formerly Ambion) Amino Ally MessageAmp II aRNA Amplification kit and GE (formerly Amersham) CyDye single reaction dye pack of the activated Cy3 and Cy5 dyes. The following steps are performed in the dark and are taken from the Ambion protocol.

# Place 20 μg of amino allyl aRNA in a nuclease-free microfuge tube, and vacuum dry to completion on the low setting (takes 30-60 minutes, depending on volume). After 30 minutes, check every 5-10 minutes and remove sample as soon as it is dry; do not overdry.
# To tube containing dried aRNA, add 9 μL Coupling Buffer and mix well/flash spin.
# Resuspend each CyDye pack in 11 μL of DMSO [and keep in the dark at room temperature for up to 1 hour until ready to use it.] You will need one Cy3 and one Cy5 pack per microarray.
#* It is helpful to flash spin the dried dye before adding the DMSO to make sure it is at the bottom of the tube.
# To tube containing the aRNA:Coupling Buffer mixture, add 11 µL of dye to each tube, mix thoroughly and flash spin.
#* NOTE: Make sure you know which dye to add to which tube!
# Incubate at room temperature in dark for 30 minutes (Wrap the rack with foil and place the rack in a drawer).
# To quench the reaction, add 4.5 μL of 4 M hydroxylamine and mix well. Incubate at room temperature in the dark for 15 minutes.
# Add 5.5 μL of nuclease-free water to bring each sample to 30 μL.

'''Removing Uncoupled Dye Material'''

# Before beginning the procedure, pipet enough nuclease-free water into a fresh tube so that you have 30 μL X number of tubes, plus a little extra. Pre-heat to 55°C. The water should heat for at least 10 minutes.
# Add 105 μL of aRNA Binding Buffer to each labeled aRNA sample--proceed to the next step immediately.
# Add 75 μL of 100% ethanol to each sample, and mix by pipetting the mixture up and down 3 times. '''''Do NOT vortex and do NOT centrifuge.'''''
# Place aRNA filter cartridges into the appropriate number of collection tubes and pipet each sample from the previous step onto the appropriate column. Spin <s>1 minute at 10,000 X g</s> 2 minutes at 5,000 X g. Discard flow-through.
#* ''Note that we started having issues with the spin columns when Ambion/Applied Biosystems got purchased by Invitrogen and they started supplying Invitrogen columns in the kit. The resin would come down into the collection tube. We now spin for 2 minutes at 5,000 X g instead.''
# Apply 500 μL Wash Buffer to each filter cartridge. Spin 2 minutes at 5,000 X g. Discard flow-through.
# Spin again at 5,000 X g to remove trace amounts of Wash Buffer.
# Transfer filter cartridge into a fresh collection tube, being careful not to contaminate the new tube with any of the flow through from the previous step.
# To the center of the filter, add 15 μL of the nuclease-free water that you pre-heated to 55°C in step 1.
#* Note: the manufacturer's protocol calls for eluting twice with ''10 μL'' of the nuclease-free water, not 15 μL. However, we have observed that 5-8 μL of the total elution volume is retained on the column. By increasing the volumn slightly for each elution step we have increased our yield of labeled aRNA without diluting it too much. ''— [[User:Kam D. Dahlquist|Kam D. Dahlquist]] 12:47, 22 July 2010 (EDT)''
# Let sit at room temperature for 2 minutes, then spin for 3 minutes at 5,000 X g.
# Repeat the elution with another 15 μL of nuclease-free water pre-heated to 50-60°C.
# Let sit at room temperature for 2 minutes, then spin for 3 minutes at 5,000 X g.
# Carefully transfer eluate to a 1.5 mL microfuge tube with a lid and place on ice.

'''Determine the concentration of labeled aRNA'''

# Dilute the labeled aRNA 1:50 by placing 1 μL of labeled aRNA into 49 μL of TE Buffer in a fresh tube.
#Read A260 and A550 for Cy3 or A650 for Cy5. If A260 is below 0.1, adjust dilution and try again.
#* A calculator for RNA concentration and labeling efficiency can be found at: [http://www.b2b.invitrogen.com/site/us/en/home/support/Research-Tools/Base-Dye-Ratio-Calculator.html http://www.b2b.invitrogen.com/site/us/en/home/support/Research-Tools/Base-Dye-Ratio-Calculator.html]
#* Alternately, read 2 μL of sample directly on an [http://www.implen.com/nanophotometer.html Implen NanoPhotometer] using the 0.2 mm lid (factor 50). It will compute the labeling efficiency automatically for you.
#* If you had multiple tubes of reference sample, and they all look OK on the spec, mix them together and re-read them as a single mixed sample.
# Calculate the volume required for 5 μg of Cy3 and Cy5 labeled aRNA. Mix those volumes of the appropriate Cy3 and Cy5 labeled aRNA together.
#* NOTE: Be sure to mix the right samples together!

'''Preparation for hybridization'''

# Vacuum dry the labeled aRNA that will be used for hybridization in a speedvac until the volume reaches 1-9 μL. Do not overdry (Check every 5 minutes.)
# If necessary, bring the volume of the dried labeled aRNA to 9 μL with nuclease-free water.
# Add 1 μL of Ambion 10X Fragmentation Buffer to the labeled aRNA.
# Incubate at 70°C for 15 minutes.
# Add 1 μL of the Stop Solution and place on ice.
# Speedvac the fragmented aRNA until the volume is < 5 μL. This will take about 5 minutes. Do NOT overdry.
# Make the hybridization master mix as follows:
X1 X6
DIG Easy Hyb solution 100 μL 600 μL
1 μg/μL oligo dA 0.38 μL 2.28 μL
10 mg/mL sonicated salmon sperm DNA 5 μL 30 μL
# Mix and flash spin. Incubate at 65°C for 2 minutes. Let cool until room temperature.
# Add 85 μL of the hybridization master mix to the paired, dried sample. Incubate at 65°C for 2 minutes. Flash spin and let cool until room temperature.
# Place the cover slip with the smooth side up on a support (a rack for 15 mL test tubes works great). Have the microarray slide ready with the hybridization chamber. Pipet the hybridization solution in a line on the cover slip, avoiding the introduction of air bubbles. Holding the microarray slide only by the edges (do not touch the front or back of the slide), pick up the cover slip with the DNA side of the slide down (the label side is the DNA side) and quickly invert the slide and place in the chamber with the DNA side and cover slip up.
# Pipet 11 μL of nuclease-free water into the wells in the hybridization chamber on either side of the slide. Place the cover on the chamber and lock the clips in place.
# Working quickly and keeping the hybridization chamber horizontal, place the chamber at the bottom of the 37°C water bath. Incubate for 15-16 hours.

=== Day 5 ===

'''Post-hybridization washing and scanning'''

# Remove the hybridization chamber from the water bath and dry the outside with a large kim wipe. Pull the clamps off and wipe again before opening the chamber. Lift the slide from the barcode end using forceps. Remove the coverslip by quickly, but gently dipping the slide in a 50 mL conical tube filled with room temperature 1X SSC. Let the coverslip slide off gently; hold the slide at the barcode end with forceps. Once the cover slip comes off, transfer the slide to another conical tube filled with 50°C 1X SSC/0.1% SDS. Incubate for 15 minutes in the 50°C waterbath.
# Transfer slide quickly to a second tube filled with 50°C 1X SSC/0.1% SDS. Do not let the slide dry out while transferring. Incubate for 15 minutes in the 50°C waterbath.
# Transfer slide quickly to a third tube filled with 50°C 1X SSC/0.1% SDS. Do not let the slide dry out while transferring. Incubate for 15 minutes in the 50°C waterbath.
# After the three washes are complete, rinse the slide in a tube filled with room temperature 1X SSC by plunging up and down 4-6 times.
# Rinse the slide in a tube filled with room temperature 0.1X SSC by plunging up and down 4-6 times. When you pull the slide out the last time, pull it out very slowly so that water droplets do not form on the surface of the slide. Then carefully blot the edges of the slide dry on a folded kim wipe, being careful not to touch the front or back surface of the slide. Use the compressed air duster to blow off any water droplets that remain. You are not blowing the water dry, but chasing it to the edge of the slide so that it can be blotted by the kim wipe.
# Carry the dry slide in a slide box covered in foil to the fume hood in the Keck Lab. Dip the slide into the coplin jar filled with 2% PEG (2000) in 1:1 acetone:toluene. Be careful not to dip the label into the solvent. Work quickly. Allow the slide to dry for about 1 minute before putting it back in the box and bringing it back into the Dahlquist lab for scanning. Keep the slide in the dark until scanning.

'''Scanning with the Axon GenePix 4000B Scanner'''

# Make sure that the computer is OFF before turning on the scanner.
# Remove the dust cover and turn on the scanner using the switch on the black box in the back of the scanner.
# Turn on the computer and login to the username “scanner”. Ask Dr. Dahlquist for the password.
# Let the scanner warm up for 15 minutes before scanning.
# See the pictures on the cabinet above the scanner for how to insert the slide. Be gentle!
#* The DNA side of the chip should be down and the barcode should be facing towards the front of the instrument.
# Open the Hardware Settings window (click the icon on the right-hand side that looks like the scanner with a key hanging off of it.)
# Make sure that the pixel size is set to 10, lines to average is set to 2, and focus position is set to 0. Set the PMT Gain for the 635 wavelength to 650 and the PMT Gain for the 532 wavelength to 550. The Power should be at 100% for both.
# Perform a Preview Scan by clicking the icon with the double arrows (looks like a "fastforward" icon).
#* While it is scanning, click on the histogram tab to see the Count Ratio of red to green signal. It should be within 10% of 1.00 (0.90 to 1.10). You can adjust the PMT Gain settings in the Hardware Settings window to adjust this ratio. The histogram tab will show you the data for the area of the image that is selected in the main Image window, so if you change the settings, you need to zoom to the area in which that setting applies.
#* Allow the Preview Scan to complete, so that the instrument will read the barcode. If it does not register the bar code, double-click on the barcode area at the bottom of the screen to enter it manually.
# Perform a Data Scan by clicking on the single arrow (second icon down on the right-hand side of the window). It will take ~10 minutes to complete the scanning of the slide.
# Save the data by clicking on the floppy/folder icon on the right hand side and choosing "Save Images" from the menu that appears.
#* In the dialog box that appears, make sure that the images are being saved as "Single-image tiffs". Use the barcode and date as part of the file names. Create a folder for today's date (yyyymmdd) in the C:\MicroarrayData folder to save the files.
# When you are finished scanning, turn off the scanner so that we do not wear out the laser and replace the dust cover.
# Go to the [[Dahlquist:GenePix_Pro_Software_Protocol | GenePix Pro Software Protocol]] for gridding the image and generating the data.

Main Page

2024-05-02T19:42:27Z

Kdahlquist: /* Students */ add class picture

__NOTOC__
<div style="text-align: center; font-size: 175%">Loyola Marymount University</div>
<div style="text-align: center; font-size: 250%; line-height: 1.25em">'''BIOL 367-01: Biological Databases'''</div>
<div style="text-align: center; font-size: 175%; margin-bottom: 0.85em">Spring 2024</div>

<div style="float: right;">__TOC__</div>

== Announcements ==

* Don't forget to sign your class journal entries with your wiki signature! '''<nowiki>~~~~</nowiki>'''

=== Upcoming Seminars ===

''There are no more seminars for the remainder of the semester.''



== Instructor ==
* [[User:Kdahlquist|Kam D. Dahlquist]]

== Students ==

{| style="margin-left: auto; margin-right: auto"
| style="padding-right: 1em" | [[User:Hivanson| Hailey Ivanson]]
| style="padding-right: 1em" | [[User:Asandle1| Andrew Sandler]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Ckapla12| Charlotte Kaplan]]
| style="padding-right: 1em" | [[User:Nstojan1| Natalija Stojanovic]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Kmill104| Katherine Miller]]
| style="padding-right: 1em" | [[User:Msymond1| Dean Symonds]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|}

[[Image:BIOL367_Spring2024_class-picture_reduced.jpg|600px|thumb|center|Left to right: Dr. Dahlquist, Natalija, Hailey, Charlotte, Katie, Dean, Andrew]]

{{Final Project Links}}

== Schedule ==

The current course schedule is shown below. In addition to the listed in-class agendas, the following guidelines are also notable:

* Unless otherwise stated on the schedule, your weekly journals/assignments are due on Thursdays at 12:01am. In cases where subsequent revisions or corrections will be accepted, the instructor will provide feedback and submission deadlines on a per-assignment basis.
* Reading assignments should be completed ''before'' coming to class.

{| class="wikitable"
|-
! Week 
! Date 
! Before Class Reading 
! During Class Topic
! After Class Assignment
|- style="vertical-align:bottom;"
| rowspan="2" | 1
| 9-Jan
| 
|
* Syllabus walkthrough
* Pairwise interviews and introductions
* Academic Honesty case studies
* Wiki account setup
| rowspan="2" | [[Week 1]] (due 12:01am 1/18) [[Class Journal Week 1]] 
|- style="vertical-align:bottom;"
| 11-Jan
| [https://peerj.com/preprints/3215v1/ Dahlquist et al. (2017) ''An Invitation to Modeling'']
|
* What is a model?
* Model of a cell/model of a computer 
|- style="vertical-align:bottom;"
| rowspan="2" | 2
| 16-Jan
|
* Denning [http://dl.acm.org/ft_gateway.cfm?id=1378711 ''Voices of Computing''], [http://dl.acm.org/ft_gateway.cfm?id=1272529 ''Computing is a Natural Science''] (also available on [http://brightspace.lmu.edu/ Brightspace]).
* Janovy ''On Becoming a Biologist'' Chapter 1, available on [http://brightspace.lmu.edu/ Brightspace].
* Note that there are some ''before'' questions you should answer before completing these readings. See [[Week 1]].
|
* Discuss the Week 1 assignment
** Wiki syntax overview
** Lab session to setup User wiki page 
| rowspan="2" | [[Week 2]] (due 12:01am 1/25) [[Class Journal Week 2]] 
|- style="vertical-align:bottom;"
| 18-Jan
|
* [http://www.ncbi.nlm.nih.gov/books/NBK21134/#A5234 Brown, T.A. (2002) Ch. 1 ''Genomes 2'']
* [http://www.ncbi.nlm.nih.gov/books/NBK21121/ Brown, T.A. (2002) ''Genomes 2'', Ch. 3, especially section 3.3.2]
| DNA structure
|- style="vertical-align:bottom;"
| rowspan="2" | 3
| 23-Jan
|
* On [http://brightspace.lmu.edu Brightspace]:
** [https://www.sciencedirect.com/science/article/pii/S0968000403003025 Nirenberg (2004) ''Deciphering the Genetic Code'']
** [https://www.cell.com/trends/biochemical-sciences/fulltext/S0968-0004(04)00083-0 Kaji & Kaji (2004) ''Setting the Record Straight'']
** Moody (2004) ''Digital Code of Life'', Ch. 1
** Hayes (2004) ''Ode to the Code''
| Aipotu work session
| rowspan="2" | [[Week 3]] (due 12:01am 2/1) [[Class Journal Week 3]] 
|- style="vertical-align:bottom;"
| 25-Jan
| 
|
* Genes as models
* Central model of molecular biology
** [http://www.youtube.com/watch?v=u9dhO0iCLww Berkeley translation video]
** This [https://dnalc.cshl.edu/resources/animations/ web site] has links to animations of the replication, transcription, and translation processes.
** [http://brightspace.lmu.edu Slides on Brightspace]
* [[Media:BIOL367_Spring2024_GeneticCode-CentralModel.pdf | Paper and pencil exercise]]

|- style="vertical-align:bottom;"
| rowspan="2" | 4
| 30-Jan
|
* [http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/ Ford, Paul. “What is Code?” ''Business Week'', June 11, 2015.]
* [[Media:L01_DataManagement.pptx | DataONE: Data Management Slides]]
|
Introduction to biological databases ([[Media:2024-01-30_biological-databases-part1.pdf | part 1 slides]]) 
* What is bioinformatics?
* Open Science Ecosystem
* DataONE: Data management and the life cycle of data
* Terminology, types, four "Gold Standard" databases
| rowspan="2" | [[Week 4]] (due 12:01am 2/8) [[Class Journal Week 4]] 
|- style="vertical-align:bottom;"
| 1-Feb
|
* [[Media:L02_DataSharing.pptx | DataONE: Data Sharing Slides]]
* [https://doi.org/10.1093/nar/gkad1173 Rigden & Fernández (2024) ''NAR'' Database Issue editorial]
|
Introduction to biological databases ([[Media:2024-02-01_biological-databases-part2.pdf | part 2 slides]]) 
* A closer look at evaluating biological databases
* DataONE: Data sharing
|- style="vertical-align:bottom;"
| rowspan="2" | 5
| 6-Feb
| 
|
* Presentation Guidelines ([https://brightspace.lmu.edu .pptx is on Brightspace])
* Week 4 work session 
| rowspan="2" | [[Week 5]] (due 12:01am 2/15) [[Class Journal Week 5]] 
|- style="vertical-align:bottom;"
| 8-Feb
| 
|
Database presentations
* [[Media:Nemo_presentation.pdf | NeMO by Hailey & Dean]]
* [https://docs.google.com/presentation/d/1C74eHcvpTo0rnbQFcUnDsmG_AIPpIqLvM0t-DV95Obk/edit#slide=id.g1f0192797b8_0_30 Monarch Initiative by Katie & Andrew]
* [[Media:The_AgeAnnoMo_Database.pdf | AgeAnnoMO by Charlotte & Natalija]]

|- style="vertical-align:bottom;"
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 2: Going Deeper (Gene Expression Data and Relational Databases)'''
|-
| rowspan="2" | 6
| 13-Feb
|
* Moody (2004) ''Digital Code of Life'', Ch. 6 (on [https://brightspace.lmu.edu Brightspace])
* Original (2001) Human Genome Project articles in [https://www.nature.com/nature/volumes/409/issues/6822 ''Nature''] & [https://www.science.org/toc/science/291/5507 ''Science'']
* Special issues (2021) "The Human Genome at 20" in [https://www.nature.com/collections/febigehfbg ''Nature''] & [https://www.science.org/toc/science/371/6529 ''Science'']
| Human Genome Project
| rowspan="2" | [[Week 6]] (due 12:01am 2/22) [[Class Journal Week 6]] 
|- style="vertical-align:bottom;"
| 15-Feb
|
|
Where's my Stuff?
* Slides are on Brightspace
* An overview of computers, networks, files, web applications, web services, and databases
* Names, URLs, identifiers
** As applied to biology: genes, species
* “Stuff” on the worldwide web
** Accessing the web on a browser
|- style="vertical-align:bottom;"
| rowspan="2" | 7
| 20-Feb
| 
| [[Week 6]] work session
* Please bring ear buds/headphones if possible.

| rowspan="2" | No Week 7 Assignment
|- style="vertical-align:bottom;"
| 22-Feb
|
* [http://www.ncbi.nlm.nih.gov/books/NBK26818/#A1633 Alberts ''et al''. (2002) ''Molecular Biology of the Cell'', Ch. 8: Microarrays]
* [https://www.youtube.com/watch?v=0ATUjAxNf6U Microarray animation]
* [https://doi.org/10.1038/4462 Brown. & Botstein (1999)]
* Campbell, A.M. and Heyer, L.J. (2003), Ch 4 ([http://brightspace.lmu.edu on Brightspace])
* [https://doi.org/10.1126/science.278.5338.680 DeRisi, et al. (1997)]
| 'omics analysis
|- style="vertical-align:bottom; background-color:#e5fee8;"
| rowspan="2" | Spring Break
| 27-Feb
| rowspan="2" colspan="3" | No class
|- style="vertical-align:bottom; background-color:#e5fee8;"
| 29-Feb
|- style="vertical-align:bottom;"
| rowspan="2" | 8
| 5-Mar
|
* [https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf Ted Codd’s seminal paper “A Relational Model of Data for Large Shared Data Banks”]
* [https://dondi.lmu.build/share/db/super-basic-database-diagramming.pdf Super basic relational database concepts]
| Guest lecture: Dr. Dionisio
* Relational Databases part 1
| rowspan="2" | [[Week 8]] (due 12:01am 3/14) [[Class Journal Week 8]] 
|- style="vertical-align:bottom;"
| 7-Mar
| [https://dondi.lmu.build/share/db/super-basic-sql.pdf Super basic SQL crib sheet]
| Guest lecture: Dr. Dionisio
* Relational Databases part 2
|- style="vertical-align:bottom;"
| rowspan="2" | 9
| 12-Mar
| 
| [[Week 8]] work session 
| rowspan="2" | [[Week 9]] (due 12:01am 3/21) [[Class Journal Week 9]] 
|- style="vertical-align:bottom;"
| 14-Mar
| 
| Transcriptomic analysis (part 1)
* ANOVA
|- style="vertical-align:bottom;"
| rowspan="2" | 10
| 19-Mar
| [https://xkcd.com/882/ "Significant"]
| Transcriptomic analysis (part 2)
* Multiple testing problem, p value corrections
| rowspan="2" | [[Week 10]] (due 12:01am 4/4, interim deadlines on 3/26 and 4/2) [[Class Journal Week 10]] 
|- style="vertical-align:bottom;"
| 21-Mar
|
* [https://academic.oup.com/bioinformatics/article/21/suppl_1/i159/203147 Ernst, J., & Bar-Joseph, Z. (2006). STEM]
* [https://doi.org/10.1038/75556 Ashburner et al. (2000). Gene Ontology]
| Transcriptomic analysis (part 3)
* Clustering and GO term enrichment analysis
|- style="vertical-align:bottom;"
| 11
| 26-Mar
|
* [https://doi.org/10.1093/nar/gkac1041 Teixeira, et al. (2023) YEASTRACT+]
* [https://link.springer.com/article/10.1007/s11538-015-0092-6 Dahlquist et al. (2015) GRNmap]
* [https://peerj.com/articles/cs-85/ Dahlquist et al. (2016) GRNsight]
|
* Transcriptomic analysis (part 4)
** GRN modeling and visualization
| rowspan="2" | Continue with [[Week 10]] assignment
|- style="vertical-align:bottom; background-color:#e5fee8;"
| Easter
| 28-Mar
| colspan="2" | No class
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 3: Integrating for Research (GRNsight Gene Expression Database Project)'''
|-
|- style="vertical-align:bottom;"
| rowspan="2" | 12
| 2-Apr
| 
| Discussion of [[Week 10]] results
| rowspan="2" | [[Week 12]] (due 12:01am 4/11) 
|- style="vertical-align:bottom;"
| 4-Apr
| 
| Begin Database Project
* Overview of project
* Work session for journal club
|- style="vertical-align:bottom;"
| rowspan="2" | 13
| 9-Apr
| 
| Work session for journal club
| rowspan="2" | [[Week 13]] (due 12:01am 4/18) 
|- style="vertical-align:bottom;"
| 11-Apr
| 
|
* Journal Club Presentations
* Work session to organize milestones
|- style="vertical-align:bottom;"
| rowspan="2" | 14
| 16-Jan
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 14]] (due 12:01am 4/25) 
|- style="vertical-align:bottom;"
| 18-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom;"
| rowspan="2" | 15
| 23-Apr
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 15]] (due 12:00 noon 5/3) 
|- style="vertical-align:bottom;"
| 25-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom; background-color:#ffccc9;"
| rowspan="2" | Finals
| 2-May
|
| '''Final Presentations 11:00am''' 
| rowspan="2" |
|- style="vertical-align:bottom; background-color:#ffccc9;"
| 3-May
|
| '''Project Deliverables Due 12:00 noon''' 
|}

== Course Information ==

=== Instructor ===

==== [[User:Kdahlquist | Kam D. Dahlquist, Ph.D.]] ====
: http://kdahlquist.github.io/DahlquistLab/index.htm
: '''Phone:''' (310) 338-7697
: '''E-mail:''' kdahlquist at lmu dot edu
: '''Office:''' Life Sciences Building 289
: '''Office Hours (Spring 2024):''' Mondays 2:00-3:30 PM, Tuesdays 3:15-4:45, and by appointment; check [https://brightspace.lmu.edu Brightspace] for a Calendly link to make an appointment for a Zoom or in-person meeting.

=== Prerequisites/Recommended Background ===

BIOL 201 and MATH 123 or MATH 132 or MATH 204 or MATH 205.

=== Class Meetings and Attendance ===
TR 1:45-3:00pm, Seaver 120 

This is a hands-on, participatory course, thus attendance at all class meetings is required. Each student is allowed two “sick” days (automatically excused absences) during the semester. Further unexcused absences from class will result in a 12 point (2.5%) deduction from the overall course grade for each absence. Every effort should be made to attend class on oral presentation days as the content of that day's class is dependent on student participation. Unexcused absences from an oral presentation will result in a grade of zero for the presentation. The instructor should be notified as soon as possible, electronically or by phone, of the reasons for all absences.

Note that the last day to add or drop a class without a grade of W is January 12. The withdrawal or credit/no-credit status deadline is April 5.

=== Mutual Responsibilities ===

This course is designed to foster your development as a biologist and computer scientist and to give you an authentic research experience. We will be engaged together in discovering, examining, and practicing the personal qualities, technical skills, and community standards of the scientific community. While you are ultimately responsible for your own learning, you are not alone. Our class constitutes a team where we will be learning from each other. The role of the instructor is to provide the expert coaching to support and assist you on your journey. All of the exercises, readings, assignments, and policies detailed below have been designed with this purpose in mind.

=== Classroom Conduct ===

We are all responsible for maintaining a classroom and laboratory environment that is safe and conducive to learning. As such, we will observe the following:

# As an LMU Lion, by the [http://studentaffairs.lmu.edu/wellness/lmucares/aboutlmucares/livethelionscode/ Lion’s code], you are pledged to join the discourse of the academy with honesty of voice and integrity of scholarship and to show respect for staff, professors, and other students.
# You are responsible for your own learning and for being a good class citizen.
# Class will start promptly on time.
# You are expected to come to class having done the assigned reading and preparatory work so that you are ready to participate in discussions and to perform the laboratory exercises.
# You are expected to bring the required materials to each class session.
# Cell phones and other ancillary devices must be turned off and put away out of sight. Your own laptop and/or tablet may be used to conduct the class exercises, '''''provided that you have confirmed with the instructor that you have the correct versions of software installed for the exercise'''''. If, however, the laptops/tablets are being used for other purposes and become distracting to you or others, you will be asked to put them away.
# All students are governed by the [https://lmu.box.com/s/urox7s2vkxtoofg0rmmnv5h7ik5rahof Student Conduct Code]. Disruptive behavior which is persistent or significantly interferes with classroom activities may be subject to disciplinary action. A student may be referred to the Office of Student Judicial Affairs if his or her behavior constitutes a violation of the conduct code.

=== Course Website ===

This is the course web site and wiki, hosted by http://xmlpipedb.cs.lmu.edu/biodb/spring2024/. You will need to have a user account on this wiki to be able to edit the wiki and complete coursework. Updates to the course schedule and electronic copies of all handouts, assignments, and readings will be posted to this site. You will also use the site to keep an electronic lab notebook/journal for the course. In addition, students have been automatically enrolled in the course page on [http://brightspace.lmu.edu Brightspace]. The site will be used for materials that cannot be made public on this wiki, including grades.

=== Email Communication ===

At times I will communicate with the entire class using campus email systems, so it is essential that you regularly check your lion.lmu.edu email address or forward your lion account email to your preferred email address. Messages sent to the instructor at night or on the weekend will be answered the next school day.

=== Required Materials ===

==== Texts ====

There is no required text to purchase for the course; materials will be put on reserve at Hannon Library or will be available online on this wiki or [http://brightspace.lmu.edu Brightspace] site. Specific reading assignments are given on the course schedule and should be completed before coming to class.
* Assorted handouts, articles, and sample code will be distributed throughout the semester.
* Additional information is also available on the web; do not hesitate to look for further sources of information regarding the concepts, techniques, tools, and paradigms that we will discuss.

==== Materials (must be brought to each class meeting) ====

* 3-ring binder or folder with all course handouts
* Pen, pencil, extra paper
* USB flash drive to back-up data
* Account for this wiki


=== Course Description ===

The disciplines of biology and computer science come together in bioinformatics, where computational tools are needed to manage and analyze the flood of data coming from new genomics technologies. Biological databases form a significant part of this young and exciting field. This course introduces students to both the biology and computer science expertise needed to understand, use, and develop biological databases. Biology topics include the fundamentals of genetics, molecular biology, and biochemistry needed to understand the data stored in biological databases, as well as the biotechnologies used to gather these data in a high-throughput manner. Computer science topics include what biological databases are, why they are important (and needed), and the challenges that arise in compiling them effectively. Biology and computer science lectures on topics that are relevant to biological databases are coupled with hands-on experience with a variety of software packages ranging from bioinformatics utilities to general-purpose database and software development tools. After learning how to use a biological database, students will be asked to build one of their own.

==== Course Objectives and Learning Outcomes ====

This course is built upon L. Dee Fink’s ''taxonomy of significant learning'', as applied to biological databases. Long after the course concludes, our hope is that:
* You understand how biological information is encoded in the genome and can apply this knowledge to a variety of biological tasks and problems
* You understand the core concepts, structure, and functions of a database, ranging from individual files to a full relational database management system, and can perform useful tasks with such data
* You show discipline and proficiency in day-to-day science and engineering best practices, such as maintaining journals and notebooks, managing your files and code, and critically evaluating scientific and technical information
* You recognize and care about how the biological and technological issues presented in this course relate to and affect society, our daily lives, and ourselves
* You have some skills and tools for “leaving your comfort zone,” flourishing outside of it, and learning more about biology and computer science on your own
* You learn how to communicate and work effectively with colleagues from your discipline and different disciplines

==== University Core Curriculum ====

This course fulfills the following requirements in the University Core Curriculum:
* Integrations: Interdisciplinary Connections

=== Course Work and Grading ===

Your work in this course will be assessed in the following areas:

{| style="border: 1px dashed rgb(47, 111, 171); background: rgb(249, 249, 249); margin: 1em 0; padding: 1em" cellpadding="5ex"
| Weekly electronic lab notebook/journal assignments, individual (usually 12 points each)
| style="text-align: right" | 168 
| points
|-
| Weekly electronic lab notebook/journal assignments, shared (usually 3 points each)
| style="text-align: right" | 42 
| points
|-
| Oral presentations (3 @ 35, 45, 60 points)
| style="text-align: right" | 140
| points 
|-
| Final Project Deliverables (including written report)
| style="text-align: right" | 100
| points
|-
| '''Total'''
| style="text-align: right" | '''450''' 
| '''points'''
|}

Final course grading scale:
94.0-100.0% A
90.0- 93.9% A-
86.0- 89.9% B+
82.0- 85.9% B
78.0- 81.9% B-
74.0- 77.9% C+
70.0- 73.9% C
67.0- 69.9% C-
60.0- 66.9% D
≤ 59.9% F

Current grades will be made available at [http://brightspace.lmu.edu Brightspace].

==== Electronic Laboratory Notebook/Journal ====

One of the most important skills you can develop as a scientist is keeping an excellent laboratory notebook. For computational research, the equivalent of the biology paper-based lab notebook is documentation of your “workflow.” For this course you will practice documentation skills by keeping an electronic lab notebook or journal. The technology we will use is this wiki that we will create and edit during the semester. The wiki software is the same one that runs Wikipedia and many other wiki sites, so proficiency gained here is easily transferable to other applications.

You will create an individual user page and make weekly entries that the instructor will read and grade. You will use the wiki to complete the assignments as well. The following guidelines apply:
* Your weekly journal entry is typically due every 12:01am on Thursday Pacific time; consult the schedule for specific due dates for each assignment.
* Each weekly assignment has an individual component and a shared component. You will earn 12 points per weekly submission for the individual journal entry and 3 points per submission for the shared journal entry. '''''Late journal entries will be accepted up to one week later for up to half credit.'''''
* The instructor will read and comment on how to improve your journal entries on your user talk pages.
* Depending on the type of assignment for that week, you may be given the opportunity to make improvements to previous journal entries as the semester progresses.
* For most weeks in the semester, you will be assigned a "homework partner". You will be expected to consult with your partner in order to complete the assignment. However, unless otherwise stated, each partner must submit his or her own work as the individual journal entry (direct copies of each other's work is not allowed).
* Generally, your journal entries will consist of:
** Your electronic laboratory notebook (workflow and other documentation) for hands-on exercises and projects
** Answers to any specific questions posed in the exercise
** Acknowledgments section (see [[Week 1]] assignment for details)
** References section (see [[Week 1]] assignment for details)
** Shared reflection on your learning, assigned readings, or ethics case studies.

==== Oral Presentations ====

You will give three oral presentations in this course. The first two will be in the format of a “Journal Club” presentation where students will present and lead discussion of research articles from the primary literature. The third will be a research presentation on your final project. '''''Because that day’s class content is dependent upon each student being ready to present and lead discussion, late journal club presentations will not be accepted. An unexcused absence from a journal club presentation will result in a grade of zero for the presentation.'''''

==== Final Group Project ====



In addition to the research presentation, the culmination of your final project will be the preparation of a written laboratory report in the style of a manuscript that could be submitted to a peer-reviewed journal. Specific instructions will be posted later in the semester. '''''The Final Written Report cannot be accepted any later than Friday, May 3 at 12:00pm. The Final Written Report must be completed to receive a passing grade in the course.'''''

==== Life happens, what do I do then? Use your tokens! ====

To succeed in this course it is important to come to each class session and keep up with the work. However, I understand that circumstances may arise from time-to-time that could interfere with this. To responsibly manage these circumstances, the following token system is in place.

* Each student begins the semester with 4 tokens that can be used as follows:
** 1 token = turning in a individual journal entry up to one week later without penalty '''''or''''' dropping a missed shared journal entry from the final grade without penalty.
** 3 tokens = dropping a missed individual journal club entry from the final grade without penalty.
** 4 tokens = excusing an absence without penalty beyond the two automatically excused.
* To use tokens, the instructor must be emailed about your intention to use the token(s) at the day/time of usage (due date or absence). Requests to use tokens after one week from the due date or absence has passed will not be honored. Unused tokens have no point value.
* Up to two additional tokens may be earned by attending extra credit seminars (see below).

==== Extra Credit ====

Students may accumulate up to 12.5 points toward their final grade in extra credit by attending Biology Department seminars and completing the seminar sheets. Each seminar attended is worth 2.5 points with up to 5 seminars (12.5 points) total.

Alternately, you may elect to earn a token for attending the seminar instead of the extra credit points. Only two tokens may be earned this way, and the instructor must be notified of your intention to earn a token instead of extra credit at the time of the seminar by writing it on the seminar sheet on the day of the seminar.

Certain non-Biology Department seminars may be approved in advance for extra credit at the instructor's discretion. To receive credit for these seminars, you must turn in a one-page '''''hard copy''''' of your summary of the seminar '''''in class, within one week''''' of the date of the seminar or they will not count as extra credit.

===== Biology Department Seminar Attendance Policy =====

* To receive course credit for attending a Biology Department Seminar, students must do the following:
** Arrive early at the seminar venue (usually FEA auditorium) and obtain a paper seminar sheet from a faculty member.
*** Seminar sheets will only be available until 3:05 PM, at which time no further sheets will be distributed.
*** You must pick up the seminar sheet yourself. You may not obtain seminar sheets for others.
** Completely fill out the seminar sheet during the seminar, including:
*** Your name as it appears on PROWL
*** All course numbers, section numbers, professor and TA names for the courses for which you would like to receive credit
*** Day and time of seminar, speaker name, and title
*** Answer the other questions on the seminar sheet.
** Stay quietly in your seat for the entire seminar, including the question and answer period.
** At the end of the seminar, take a picture of the seminar sheet and upload it to the survey link accessed via a posted QR code.
** Turn in the paper seminar sheet to a faculty member before exiting the room.
*** You must turn in your own seminar sheet; you may not turn it in for someone else.
* Note that students arriving after 3:05 PM will not receive a seminar sheet and must enter through the back entrance on the second floor of the FEA auditorium so as not to disturb the seminar in progress.

=== Work Load Expectations ===

In line with [https://academics.lmu.edu/media/lmuacademics/provost/documents/LMU%20Credit%20Hour%20Policy_Final.pdf LMU’s Credit Hour Policy], the work load expectation for this course is that for every one hour (50 minutes) of classroom instruction, you will complete a minimum of two hours of out-of-class student work each week. This is a 3-unit course with 3 hours (150 minutes) of instruction per week. Thus the expectation is that you will complete 6 hours of work outside of class per week.

=== University Policy on Academic Honesty ===

Loyola Marymount University is a community dedicated to academic excellence. Academic honesty in scholarship and creative work stands at the center of LMU's academic life, and is essential for true learning and creation of knowledge to take place. As a university in the Jesuit and Marymount traditions, this community expects its members to act in accordance with the highest standards of honesty and ethics at all times. Violations of academic honesty undermine the fundamental educational mission of the University and cannot be tolerated.

Academic dishonesty will be treated as an extremely serious matter with severe consequences. '''''The minimum penalty for an instance of academic dishonesty in this course, even on a 1-point assignment or extra credit assignment, is a one-letter grade penalty in the course and a zero on the assignment.''''' It is never permissible to turn in any work that has not been authored by the student, such as work that has been copied from another student or copied from a source (including the Internet) without properly acknowledging the source. Note that students may not submit assignment or paper prompts to CourseHero, Chegg, online artificial intelligence tools, or any other such website; answers or papers derived from such sites are considered to be a direct violation of the Academic Honesty policy. It is the student's responsibility to make sure that your work meets the standard set forth in the “Academic Honesty Policy” (see http://academics.lmu.edu/honesty.) You are responsible for contacting the instructor before assignments are due to proactively resolve any questions you may have.

You are required to sign the [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]] for this course.

==== Academic Honesty Resources ====
* [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]]
* [https://academics.lmu.edu/media/lmuacademics/academichonesty/documents/Academic-Honesty-Policy-2021.pdf LMU Academic Honesty Policy and Procedures]
* [http://www.bio.davidson.edu/dept/plagiarism.html The Davidson College Department of Biology Guidelines for Using and Citing Sources]
* [[Media:BIOL367_Spring2024_GuidelinesforLiteratureCitations.pdf | Guidelines for Literature Citations in a Scientific Paper]]
** [https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_basic_rules.html APA Style for References]
* [http://dondi.lmu.build/share/misc/plagiarism.pdf Notes on plagiarism from an electrical engineering & computer science perspective]
* [http://libguides.lmu.edu/BIOL367 BIOL/CMSI 367 LibGuide]

=== Americans with Disabilities Act—Special Accommodations ===

Students with special needs who require reasonable modifications, special assistance, or accommodations in this course should promptly direct their request to the Disability Support Services (DSS) Office. Any student who currently has a documented disability (ADHD, Autism Spectrum Disorder, Learning, Physical, or Psychiatric) needing academic accommodations should contact the DSS Office (Daum Hall 2nd floor, 310-338-4216) as early in the semester as possible. All discussions will remain confidential. Please visit http://www.lmu.edu/dss for additional information. In addition, please schedule an appointment with the instructor early in the semester to discuss any accommodations for this course for which you have been approved.

=== Health and Wellness ===

There are many resources for student wellness on campus. A central website for students is: http://lionwellness.lmu.edu.

==== COVID-19 ====

All University mandated COVID-19 safety guidelines are to be followed. The [https://www.lmu.edu/together/ LMU Together] and [https://www.lmu.edu/together/resources/matrix/ Need to Know A-Z Index] websites contain updated information. If you have COVID-19 symptoms and/or test positive, please contact the COVID Support Team ([mailto:COVIDSupportTeam@lmu.edu COVIDSupportTeam@lmu.edu] or 310-568-6868) for instructions.

=== Emergency Preparedness ===

To report an emergency or suspicious activity, contact the LMU Department of Public Safety by phone (x222 or 310-338-2894) or at the nearest emergency call box. In the event of an evacuation, follow the evacuation signage throughout the building to the designated safe refuge area where you will receive further instruction from Public Safety or a Building Captain. For more safety information and preparedness tips, visit http://www.lmu.edu/emergency.

=== Revision Notice ===

If necessary, this syllabus and its contents are subject to revision; students are responsible for any changes or modifications announced in class. The most current version of this information resides on this page, the course web site at http://xmlpipedb.cs.lmu.edu/biodb/spring2024/.

File:BIOL367 Spring2024 class-picture reduced.jpg

2024-05-02T19:39:46Z

Kdahlquist: Class picture taken 2024-05-02

== Summary ==
Class picture taken 2024-05-02

Yeast Beasts

2024-05-02T18:06:06Z

Kdahlquist: link to final version of presemation

* This page will be the main place from which the Yeast Beasts team project will be managed. Include all of the information/links that you think will be useful for your team to organize your work and communicate with each other and with the instructors. ''Hint: the kinds of things that are on your own User pages and on the course Main page can be used as a guide.''

[[Media:Yeast_Beasts_Presentation.pdf | Final version of presentation]]

==Week Reflections==
===Week 13===
====[[User:Hivanson|Hailey's]] Reflection [Quality Assurance]====
*I worked closely with Charlotte and Katie toward completing Milestones 2 and 3. We completed milestone 2 and are close to completing milestone 3.
*I thought it worked well to split up, with Natalija going with the coder/designers and me going with data analysis, ''but'' I would love to see where they are at on their progress so that we can join up for the upcoming milestone 4. I want to do this on or before next Tuesday, April 30th.
*It did not work to try to do tasks simultaneously with the data analysts. To fix this, we had one person with an open Excel sheet on their computer, another reading and checking off the steps, and another checking that all of the data and equations were being entered properly. This solution worked well for us and we will continue to have just one computer with Excel open on it, but switching roles between the person inputting data and the one checking off steps could be better for the future.

[[User:Hivanson|Hivanson]] ([[User talk:Hivanson|talk]]) 23:35, 17 April 2024 (PDT)

====Andrew's Reflection [Coder/Designer]====
To find my electronic notebook for this week please click on [[Asandle1 Week 13#Electronic Lab Notebook|Andrew Sandler's Week 13 Lab Notebook]]
'''Executive Summary'''

#Classified Significant P-values as 1 (P < 0.01) or '0'
#Found issues with data including missing gene descriptions.
#Initially tried to use Yeastmine to find the missing gene information but it was inefficient.
#Found additional blanks in the dataset and need to speak with Dr. Dahlquist about how to solve this issue.

'''What worked?'''
Everything "worked" but some surprises came up.

'''What didn't work?'''
Not that this didn't work but it provided a challenge, the issues with the #REF boxes, the blank boxes, the random text in some boxes, and the NaN coming up in some spots. I don't know how to deal with this and will need help from Dr. Dahlquist so I am not just guessing at a solution. I also need to figure out how to get a complete Gene ID list and then compare the whole ID list to the missing ID's. I also need that list for the ID's for the Access Database.

'''What will I do next to fix what didn't work?'''
I plan on speaking with Dean and Dr. Dahlquist in class tomorrow to fix these issues and then move onto working on the Access section of this assignment.

[[Category:Journal Entry]]
[[Category:Team Project]]

====Dean's Reflection [Coder/Designer]====
# This week, me and my partner completed milestones 1 and 2, and we are currently working on milestone 3, there are some complications in milestone 3, for a large part of it requires Microsoft Access, and there are also some issues in importing tables to excel. [[MSymond1]]
# Each team member should reflect on the team's progress:
## The things that worked well are cleaning up the data for the network table, which was done in class on Tuesday, the data table looks much more organized and the p values have all been successfully converted
## The other data tables are not pasting into excel as neatly as anticipated, I am also unaware of how to obtain the data from the yeastmine website.
## To fix these issues, I will ask Dr. Dahlquist for further advice in class on Thursday.
[[User:Msymond1|Msymond1]] ([[User talk:Msymond1|talk]]) 13:33, 18 April 2024 (PDT)

====Katie's Reflection====
#This week, Charlotte, Hailey, and I worked on completing Milestones 2 and 3. These milestones consisted of preparing the dataset from SGD for analysis, and then performing an ANOVA analysis like we had done in Week 9. A more detailed summary of the steps we followed is outlined on mine and Charlotte's individual page, linked below.
#* [[Data Analysts Week 13]]
#The data analysts, me and Charlotte, worked together with Hailey on progressing through Milestones 2 and 3 on the Data Analysis page. We contacted each other throughout the week to check in on what each person was doing. We then met in person to work together on performing the ANOVA analysis. This worked well, because when we couldn't meet we were still able to get some work done, and then once we got together we were able to ask any questions that we had. It was slightly difficult to progress through the steps in person because when attempting to work on the dataset at the same time, only one person could be actively making changes. I don't believe it is possible for this issue to be fixed, as we cannot have multiple people working at exactly the same time, because steps need to be followed in a specific order. In the future, we will continue to make sure that we split up the steps so that each person is doing an equal amount of work, and to be communicative about any questions that we have or can answer.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 23:09, 17 April 2024 (PDT)

====Charlotte's Reflection:====
[[User:Kmill104| Katherine Miller]] and I, being the data analysts, worked with Quality Assurance [[User:Hivanson| Hailey Ivanson]] to complete Milestone 2 and Milestone 3 in person on April 17th, 2024. We messaged the Coder/Designers and got an update from them. I wrote out the steps taken on our [[Data Analysts Week 13]] page. It was helpful that we were able to meet in person to collaborate. However, it was hard to make changes to the data since we were working on one computer. We ended up splitting up the work well, but at first everyone trying to make edits at once was hard. Now we know a system that works for us as a group.

[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 14:00, 18 April 2024 (PDT)

===Week 14===
===Week 15===
# Each person needs to write a short executive summary of that person's progress on the project for the week, with links to the relevant individual journal pages (which will have more detailed information).
# Each team member should reflect on the team's progress:
## What worked?
## What didn't work?
## What will I do next to fix what didn't work?
# Note that you will be directed to add specific information to your team's pages in the individual portion of the assignment for this and future weeks.

[[File:Yeast_Beasts_Presentation.pdf]]

{{Yeast_Beasts}}
[[Template:Yeast_Beasts]]

File:Yeast Beasts Presentation.pdf

2024-05-02T18:05:18Z

Kdahlquist: Kdahlquist uploaded a new version of File:Yeast Beasts Presentation.pdf

== Summary ==
Rough Draft

Data Analysts Week 14

2024-05-01T20:31:34Z

Kdahlquist: add correct template and categories

===Continuing Milestone 3===
[[User:Hivanson| Hailey Ivanson]] helped Katie and I with the Bonferroni and B-H values.
#We used the formula =IFCHP_Bonferroni_p-value>1,1,CHP_Bonferroni_p-value) and =IFControl_Bonferroni_p-value>1,1,Control_Bonferroni_p-value)
#we inserted a new worksheet named "CHP_ANOVA_B-H" and "Control_ANOVA_B-H."
#we copied and pasted the "MasterIndex", "ID", and "Standard Name" columns from our previous worksheet into the first two columns of the new worksheet.
#We used Paste special > Paste values and copied our unadjusted p values from our ANOVA worksheet and pasted it into Column D.
#We selected all of columns A, B, C, and D and sorted by ascending values, smallest to largest.
#We typed "Rank" in cell E1. we typed "1" into cell E2 and "2" into cell E3. Then we selected both cells E2 and E3 and double clicked on the plus sign to fill the column with a series of numbers from 1 to 4697.
#[[User:Hivanson| Hailey Ivanson]] assisted us in calculating the Benjamini and Hochberg p value correction. We typed CHP_B-H_p-value and repeated for the control. We copied that equation to the entire column. =(D2*4697)/E2
#We then typed "CHP_B-H_p-value" into cell G1.
#In cell G2: we used the equation =IF(F2>1,1,F2) and copied that equation to the entire column.
#We selected columns A through G and sorted them in ascending order.
#We copied column G and used Paste special > Paste values to paste it into the next column of our ANOVA sheet.
#We zipped and uploaded the .xlsx file.
#We performed a sanity check by selecting row 1: Data > Filter > Autofilter- p value less than 0.05

Sanity Check Results:
*CONTROL
How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 4697)?
3699
<.01
3219
<.001
2558
<.0001
1921
<.00001
1325;

*CHP
How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 4697)?
2863
<.01
2403
<.001
1884
<.0001
1435; 30.55%
<.00001
1076; 22.91%

===Milestone 4===
#We inserted a new worksheet and named it "CHP_stem".
#We selected all of the data from the "CHP_ANOVA" worksheet and Paste special > paste values into the "CHP_stem" worksheet.
#"Master_Index" was renamed to "SPOT". Column B named "ID" was renamed to "Gene Symbol". We deleted the column named "Standard_Name".
#We filtered the data on the B-H corrected p value to be > 0.05.
#We selected all of the rows except for the header row and deleted the rows by right-clicking and choosing "Delete Row" from the context menu. Then we undid this filter.
#We deleted all of the data columns except for the Average Log Fold change columns for each timepoint.
#we renamed the data columns with just the time and units.
#We clicked "Replace all" to remove the #DIV/0! errors.
#We saved this spreadsheet as Text (Tab-delimited) (*.txt).
#We downloaded the stem.zip file and selected "Extract all" from the menu, creating a folder called stem.
#We clicked on the "Profile GO Table" to see the list of Gene Ontology. We saved the file to our desktop.
#We clicked on the "Profile Gene Table" button to see the list of genes belonging to the profile.

4/24/24
Milestone 4
P value >0.00001
41 and 7 significant profiles

Profile 41 grnsight:
Rpn4
Gcn4
Pdr1
Xbp1
Met28
Mga2
Spt23
Bas1
Yap1
Sok2
Msn2
Crz1
Rlm1
Fhl1
Pdr3
Cbf1
Rph1
Met31
Stp1
Msn4
Tec1
Rgm1
Stp2

==Acknowledgements==
This procedure was adapted from the Data Analysis page Milestone 3 and 4 protocol, linked here: [[Data Analysis]] The procedure for Milestone 3 was also adapted from the steps outlined in the [[Week 9]] assignment page. The procedure for Milestone 4 was also adapted from the steps outlined in the [[Week 10]] assignment page. Our quality assurance, [[User:Hivanson| Hailey Ivanson]] was a key part in completing this milestone, and her help was very valuable.
Except for what is noted above, this individual journal entry was completed by Katie and Charlotte and not copied from another source.

[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 14:28, 23 April 2024 (PDT)

==References==
LMU BioDB 2024. (2024). Week 14. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_14

LMU BioDB 2024. (2024). Week 9. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9

LMU BioDB 2024. (2024). Week 10. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_10

LMU BioDB 2024. (2024). Data Analysis. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Data_Analysis

{{Yeast Beasts}}
[[Category:Journal Entry]]
[[Category:Team Project]]

Data Analysts Week 13

2024-05-01T20:30:50Z

Kdahlquist: fixed template

==Charlotte and Katie's Data Analyst Journal==

===Milestone 1===
Completed as of April 11th when we gave our Journal Club Presentation with [[User:Hivanson| Hailey Ivanson]]

===Milestone 2===
#With Quality Assurance team member [[User:Hivanson| Hailey Ivanson]], we downloaded and examined the microarray dataset: [https://sgd-prod-upload.s3.amazonaws.com/S000204389/Sha_2013_PMID_24073228.zip SGD Processed Data].
#We made a sample-data relationship table in Excel labeled "reorganized" that lists all of the samples and at which time point they were collected, and their replicate number. We came up with consistent column headers that summarize this information. We named each column either Control_LogFC_timepoint-replicatenumber or CHP_LogFC_timepoint-replicatenumber, as in Control_LogFC_0-1 and CHP_LogFC_0-1. The timepoint for each is either 0, 3 , 6, 12, 20, 40, 70, or 120, and the replicate number either 1, 2, or 3. We organized the data in a worksheet in an Excel workbook so that:
#*ID is the first column header, and within it are all of the SGD systemic names
#*Data columns are to the right, in increasing chronological order, using the column header pattern we created
#*Treatments are grouped together
#*Replicates are grouped together
#*We deleted the "EWEIGHT" row and "GWEIGHT" column.
#*We then had to undo the log-transformed raw intensity values. We first created new columns for each respective trial in the formats Control_FC_timepoint-replicatenumber and CHP_FC_timepoint-replicatenumber, as in Control_FC_0-1 and CHP_FC_0-1. We then transformed the data in the first cell of each column with the equation <code>=2^<cell designation></code>, where the cell designation is the first cell of the respective Control_LogFC_timepoint-replicatenumber and CHP_LogFC_timepoint-replicatenumber columns, and then applied this command to the remaining cells of the column.
#*We then created a new worksheet labeled "with_averages", in which we copy and special pasted the values of the columns with headers Control_FC_timepoint-replicatenumber and CHP_FC_timepoint-replicatenumber.
#*We then created new columns called Control_FC_0-avg and CHP_FC_0-avg to the right of their respective t0 timepoint trials, and then within them computed the average value of the t0 timepoint trials for the control and CHP-treated data. In the first cell below the column headed Control_FC_0-avg, we used the Excel command <code>=AVG(B2:D2)</code> and then applied this command to all cells in the column. In the first cell below the column headed CHP_FC_0-avg column, we used the command <code>=AVG(F2:H2)</code> and then applied this command to all cells in the column.
#*We then created new columns to the right of each treatment with a column header either Control_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber, as in Control_Fold_Change_3-1 or CHP_Fold_Change_3-1. We then calculated the fold change by dividing the first cell of each trial by the average t0 value for the respective treatment (control or CHP-treated), and then applying this throughout the column. To the right of each new column, we also created created columns with a column header either Control_Log2_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber, as in Control_Log2_Fold_Change_3-1 or CHP_Log2_Fold_Change_3-1. In each Log2 column, We then log2 transformed the fold changes by using <code>=LOG(cell designation, 2)</code>, where the cell designation is the first cell of the respective Control_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber columns. We then applied this throughout all of the cells in each Log2 column.

===Milestone 3===
#We created a new worksheet, naming it "CHP_ANOVA".
#We copied all the Control_Log2_Fold_Change_timepoint-replicatenumber and CHP_Log2_Fold_Change_timepoint-replicatenumber columns and special pasted only the values into the new worksheet.
#To the right of each group of either the Control or CHP replicates at one timepoint, we created columns with headers in the form Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint, where timepoint is either 3, 6, 12, 20, 40, 70, or 120.
# In the cell below the Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint headers, we typed =AVG(replicate 1 cell designation:replicate 3 cell designation), where the cell designations are the first cells of the replicate 1 at one timepoint and the replicate 3 at that same time point. This computed the average of replicate values, and we then applied this throughout the remaining cells in the column.
# To the right, we then copy and special pasted the values of each Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint columns. To the right of these, we created columns with the the headers Control_ss_HO and CHP_ss_HO.
#In the first cell below Control_ss_HO, we typed <code>=SUMSQ(B2,C2,D2,J2,K2,L2,R2,S2,T2,Z2,AA2,AB2,AH2,AI2,AJ2,AP2,AQ2,AR2,AX2,AY2,AZ2)</code> and clicked enter, and below CHP_ss_HO, we typed <code>=SUMSQ(F2,G2,H2,N2,O2,P2,V2,W2,X2,AD2,AE2,AF2,AL2,AM2,AN2,AT2,AU2,AV2,BB2,BC2,BD2)</code> and clicked enter.
#In the first cell below this header, we typed =SUMSQ for each of the time points.
#After this, we highlighted all of the LogFC data in row 2- not the AvgLogFC, and we pressed the enter key.
#We created the column headers Control_Log_FC_Time and CHP_Log_FC_Time.
#We used the equation =SUMSQ(<range of cells for logFC_t0-2>)-COUNTA(<range of cells for logFC_t0-2>)*<AvgLogFC_t0-2>^2 and hit enter for each of the rows that were not the average.
#The amount of data points we have is: 21. Number of time points we have is: 7.
#We replaced <range of cells for logFC_0-2> with the data range associated with t15 and so on for each time point.
#We replaced <AvgCHPLogFC_0-2> and <AvgControlLogFC_0-2> with the cell number that we computed the AvgCHPLogFC and AvgControlLogFC for 0-2, and the "^2" squares that value. This was repeated for each of time points across our data set.
#We created the column headers CHP_SS_full and Control_SS_full.
#Below this, we used the formula: =sum(<range of cells containing "ss" for each timepoint>) and hit enter.
#In the next two columns to the right, we created the headers CHP_Fstat and Control_Fstat as well as CHP_p-value and Control_p-value.
#Since n=21 and t=7, in the first cell of each Fstat column, we used the formula =((21-7)/7)*(<CHP_ss_HO>-<CHP_SS_full>)/<CHP_SS_full>) and hit enter. This same process was repeated for the control.
#We replaced the phrase CHP_ss_HO with the cell designation and replaced the phrase <CHP_SS_full> with the cell designation. This was also repeated for the control.
#Below the CHP_p-value header, we used the formula =FDIST(<CHP_Fstat>,7,21-7) replacing the phrase <CHP_Fstat> with the cell designation. We used this same formula for the Control_p-value column.
#We performed a sanity check by filtering our data so that the p value has to be less than 0.05.
#Before continuing, we undid any filters before we calculated the Bonferroni and p value corrections.
#We created two columns to the right called CHP_Bonferroni_p-value and Control_Bonferroni_p-value.
#We used the equations =<CHP_p-value>*4697 and =<Control_p-value>*4697
#

==Acknowledgements==
This procedure was adapted from the Data Analysis page Milestone 1, 2, and 3 protocols, linked here: [[Data Analysis]]
The procedure for Milestone 3 was also adapted from the steps outlined in the Week 9 assignment page.

Except for what is noted above, this individual journal entry was completed by Katie and Charlotte and not copied from another source.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 22:50, 17 April 2024 (PDT)
[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 13:59, 18 April 2024 (PDT)

==References==
LMU BioDB 2024. (2024). Week 13. Retrieved April 17, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_13

LMU BioDB 2024. (2024). Data Analysis. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Data_Analysis

LMU BioDB 2024. (2024). Week 9. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9

{{Yeast Beasts}}
[[Category:Journal Entry]]
[[Category:Team Project]]

Data Analysts Week 13

2024-05-01T20:29:04Z

Kdahlquist: add categories

==Charlotte and Katie's Data Analyst Journal==

===Milestone 1===
Completed as of April 11th when we gave our Journal Club Presentation with [[User:Hivanson| Hailey Ivanson]]

===Milestone 2===
#With Quality Assurance team member [[User:Hivanson| Hailey Ivanson]], we downloaded and examined the microarray dataset: [https://sgd-prod-upload.s3.amazonaws.com/S000204389/Sha_2013_PMID_24073228.zip SGD Processed Data].
#We made a sample-data relationship table in Excel labeled "reorganized" that lists all of the samples and at which time point they were collected, and their replicate number. We came up with consistent column headers that summarize this information. We named each column either Control_LogFC_timepoint-replicatenumber or CHP_LogFC_timepoint-replicatenumber, as in Control_LogFC_0-1 and CHP_LogFC_0-1. The timepoint for each is either 0, 3 , 6, 12, 20, 40, 70, or 120, and the replicate number either 1, 2, or 3. We organized the data in a worksheet in an Excel workbook so that:
#*ID is the first column header, and within it are all of the SGD systemic names
#*Data columns are to the right, in increasing chronological order, using the column header pattern we created
#*Treatments are grouped together
#*Replicates are grouped together
#*We deleted the "EWEIGHT" row and "GWEIGHT" column.
#*We then had to undo the log-transformed raw intensity values. We first created new columns for each respective trial in the formats Control_FC_timepoint-replicatenumber and CHP_FC_timepoint-replicatenumber, as in Control_FC_0-1 and CHP_FC_0-1. We then transformed the data in the first cell of each column with the equation <code>=2^<cell designation></code>, where the cell designation is the first cell of the respective Control_LogFC_timepoint-replicatenumber and CHP_LogFC_timepoint-replicatenumber columns, and then applied this command to the remaining cells of the column.
#*We then created a new worksheet labeled "with_averages", in which we copy and special pasted the values of the columns with headers Control_FC_timepoint-replicatenumber and CHP_FC_timepoint-replicatenumber.
#*We then created new columns called Control_FC_0-avg and CHP_FC_0-avg to the right of their respective t0 timepoint trials, and then within them computed the average value of the t0 timepoint trials for the control and CHP-treated data. In the first cell below the column headed Control_FC_0-avg, we used the Excel command <code>=AVG(B2:D2)</code> and then applied this command to all cells in the column. In the first cell below the column headed CHP_FC_0-avg column, we used the command <code>=AVG(F2:H2)</code> and then applied this command to all cells in the column.
#*We then created new columns to the right of each treatment with a column header either Control_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber, as in Control_Fold_Change_3-1 or CHP_Fold_Change_3-1. We then calculated the fold change by dividing the first cell of each trial by the average t0 value for the respective treatment (control or CHP-treated), and then applying this throughout the column. To the right of each new column, we also created created columns with a column header either Control_Log2_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber, as in Control_Log2_Fold_Change_3-1 or CHP_Log2_Fold_Change_3-1. In each Log2 column, We then log2 transformed the fold changes by using <code>=LOG(cell designation, 2)</code>, where the cell designation is the first cell of the respective Control_Fold_Change_timepoint-replicatenumber or CHP_Fold_Change_timepoint-replicatenumber columns. We then applied this throughout all of the cells in each Log2 column.

===Milestone 3===
#We created a new worksheet, naming it "CHP_ANOVA".
#We copied all the Control_Log2_Fold_Change_timepoint-replicatenumber and CHP_Log2_Fold_Change_timepoint-replicatenumber columns and special pasted only the values into the new worksheet.
#To the right of each group of either the Control or CHP replicates at one timepoint, we created columns with headers in the form Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint, where timepoint is either 3, 6, 12, 20, 40, 70, or 120.
# In the cell below the Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint headers, we typed =AVG(replicate 1 cell designation:replicate 3 cell designation), where the cell designations are the first cells of the replicate 1 at one timepoint and the replicate 3 at that same time point. This computed the average of replicate values, and we then applied this throughout the remaining cells in the column.
# To the right, we then copy and special pasted the values of each Avg_Control_Log_FC_timepoint or Avg_CHP_Log_FC_timepoint columns. To the right of these, we created columns with the the headers Control_ss_HO and CHP_ss_HO.
#In the first cell below Control_ss_HO, we typed <code>=SUMSQ(B2,C2,D2,J2,K2,L2,R2,S2,T2,Z2,AA2,AB2,AH2,AI2,AJ2,AP2,AQ2,AR2,AX2,AY2,AZ2)</code> and clicked enter, and below CHP_ss_HO, we typed <code>=SUMSQ(F2,G2,H2,N2,O2,P2,V2,W2,X2,AD2,AE2,AF2,AL2,AM2,AN2,AT2,AU2,AV2,BB2,BC2,BD2)</code> and clicked enter.
#In the first cell below this header, we typed =SUMSQ for each of the time points.
#After this, we highlighted all of the LogFC data in row 2- not the AvgLogFC, and we pressed the enter key.
#We created the column headers Control_Log_FC_Time and CHP_Log_FC_Time.
#We used the equation =SUMSQ(<range of cells for logFC_t0-2>)-COUNTA(<range of cells for logFC_t0-2>)*<AvgLogFC_t0-2>^2 and hit enter for each of the rows that were not the average.
#The amount of data points we have is: 21. Number of time points we have is: 7.
#We replaced <range of cells for logFC_0-2> with the data range associated with t15 and so on for each time point.
#We replaced <AvgCHPLogFC_0-2> and <AvgControlLogFC_0-2> with the cell number that we computed the AvgCHPLogFC and AvgControlLogFC for 0-2, and the "^2" squares that value. This was repeated for each of time points across our data set.
#We created the column headers CHP_SS_full and Control_SS_full.
#Below this, we used the formula: =sum(<range of cells containing "ss" for each timepoint>) and hit enter.
#In the next two columns to the right, we created the headers CHP_Fstat and Control_Fstat as well as CHP_p-value and Control_p-value.
#Since n=21 and t=7, in the first cell of each Fstat column, we used the formula =((21-7)/7)*(<CHP_ss_HO>-<CHP_SS_full>)/<CHP_SS_full>) and hit enter. This same process was repeated for the control.
#We replaced the phrase CHP_ss_HO with the cell designation and replaced the phrase <CHP_SS_full> with the cell designation. This was also repeated for the control.
#Below the CHP_p-value header, we used the formula =FDIST(<CHP_Fstat>,7,21-7) replacing the phrase <CHP_Fstat> with the cell designation. We used this same formula for the Control_p-value column.
#We performed a sanity check by filtering our data so that the p value has to be less than 0.05.
#Before continuing, we undid any filters before we calculated the Bonferroni and p value corrections.
#We created two columns to the right called CHP_Bonferroni_p-value and Control_Bonferroni_p-value.
#We used the equations =<CHP_p-value>*4697 and =<Control_p-value>*4697
#

==Acknowledgements==
This procedure was adapted from the Data Analysis page Milestone 1, 2, and 3 protocols, linked here: [[Data Analysis]]
The procedure for Milestone 3 was also adapted from the steps outlined in the Week 9 assignment page.

Except for what is noted above, this individual journal entry was completed by Katie and Charlotte and not copied from another source.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 22:50, 17 April 2024 (PDT)
[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 13:59, 18 April 2024 (PDT)

==References==
LMU BioDB 2024. (2024). Week 13. Retrieved April 17, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_13

LMU BioDB 2024. (2024). Data Analysis. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Data_Analysis

LMU BioDB 2024. (2024). Week 9. Retrieved April 23, 2024 from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9

{{Team Project}}
[[Category:Journal Entry]]
[[Category:Team Project]]

Class Journal Week 10

2024-04-30T17:18:40Z

Kdahlquist: removed assignment category

==Andrew Sandler==
'''What aspect of this assignment came most easily to you?'''
The Excel portion was easy for me because of my experience in excel and the file stuff was easy as well because I have programming and computer experience.

'''What aspect of this assignment was most challenging to you?'''
Working on a windows computer and having to sign in with my super long lmu password.

'''What (yet) do you not understand?'''
I think I have a decent understanding of most of this. I don't have all the details but I have a general picture. I would say I don't understand the log stuff and how they were gotten or if it is important to know as long as I can go through the process.

[[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]])

==Katie Miller==
'''What aspect of this assignment came most easily to you?'''
I found STEM and YEASTRACT both relatively easy to use whenever I followed the steps exactly as written in the procedure. The YEASTRACT section was the most straightforward and easy for me to complete.

'''What aspect of this assignment was most challenging to you?'''
I had trouble constructing my Gene Regulatory Network, which was because my first several attempts always had some gene being left out and not connected to any others, so I had to go back and restart the process. I also had some trouble narrowing down my 6 gene ontology terms, because I wanted to make sure I didn't use terms that had very similar meanings.

'''What (yet) do you not understand?'''
I don't really understand what impact the deletions of CIN5 or GLN3 will have on the results because I have been analyzing the wild type data. I'm excited to see how this affects the yeast response and its gene regulation. In terms of wiki skills, I still don't understand how to save files under the same name so that the multiple versions are stored in our wiki.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 23:51, 3 April 2024 (PDT)

==Hailey Ivanson==
'''What aspect of this assignment came most easily to you?'''

I found the data-driven parts of this assignment to be easy; calculations on Excel, especially when there are instructions, are intuitive for me.

'''What aspect of this assignment was the most challenging for you?'''

Aside from my weird and brief struggle with STEM, making the GRN using GRNsight was not a terrible challenge, but I found it to be tedious. Entering and re-entering all of the transcription factors with some slight modifications/additions/removals for each new GRN took me almost a whole class period.

'''What (yet) do you not understand?'''

I'm not sure I completely understand what the deletion of CIN5 transcription factor does with respect to cold shock. I know that it has a role in oxidative stress response pathways in yeast, but I don't know what the expected outcomes would be given this information. I also don't completely understand the language surrounding GO terms and definitions; I don't really understand the difference between terms and .

[[User:Hivanson|Hivanson]] ([[User talk:Hivanson|talk]]) 22:38, 3 April 2024 (PDT)

==Charlotte Kaplan==

*What aspect of this assignment came most easily to you?
Selecting GO terms and adjusting the p-values for profile 45 was relatively easy because it involved straightforward filtering in Excel to identify significant terms. After filtering, finding definitions for the selected GO terms was also straightforward using the Gene Ontology website, as it only required copying and pasting the GO IDs into the search field. Overall, this aspect of the assignment involved less technical manipulation in Excel and more direct interpretation of biological significance, making it easier to accomplish for me.

*What aspect of this assignment was the most challenging for you?
The most challenging part of the assignment was preparing the microarray data file for loading into STEM. This involved several steps I was unfamiliar with, including filtering the data based on the Benjamini-Hochberg corrected p-value, deleting rows with insignificant changes in expression, deleting unnecessary data columns, and addressing any remaining #DIV/0! errors. Additionally, saving the file in the correct format posed some difficulty, especially considering the need to turn on file extensions if not already enabled. Before this assignment, I had little to no experience with excel and Andrew helped me figure a lot out.

*What (yet) do you not understand?
I still don't feel 100% comfortable doing this in excel by myself. Having the help of Andrew (my homework partner), Dr. Dahlquist, and my peers helped me a lot.

[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 22:41, 3 April 2024 (PDT)
==Dean Symonds==
'''What aspect of this assignment came most easily to you?'''

I found many of the procedural parts of the assignment to be easy, for a lot of the data collection and calculations were very clearly laid out in the lab protocol and were relatively easy to follow.

'''What aspect of this assignment was the most challenging for you?'''

The most challenging aspect of the lab was managing all of the files and making sure that I did not create duplicates or mix up files with one another and making sure I had every file I needed at every step.

'''What (yet) do you not understand?'''

I'm not sure I understand entirely how to interpret the results from the data, these concepts are not exactly difficult, but it is a quite complex way of representing them with these softwares, which is where my confusion comes in.

[[User:Msymond1|Msymond1]] ([[User talk:Msymond1|talk]]) 23:59, 3 April 2024 (PDT)

[[Category:Shared]]

User:Asandle1

2024-04-30T16:38:34Z

Kdahlquist: remove shared category

==Andrew Sandler's User Page==

[[File:FunnyMirrorBoston.jpeg|200px|thumb|right|Me and my cousins in a mirror in boston]]

;Contact:
:Electronic Mail: asandle1 at the lmu email domain you all know and love
:LMU Snail Mail: Hilton Center for Business 1 LMU Drive, MS 8385. Los Angeles, CA 90045-2659

;Education:
:Major: Entreprenuership
:Graduation: 2024
;Career:
:Goals:'''
::*Work with Brain Human Interfaces
::*Work in Health Tech
::*Contribute to Saving Lives and the Planet
::*Directly interface Human's with AI
::*Improve Human cognition
:Independent Research:
::*No independent research projects (Yet)
;Work Experience
:Sales Rep
::*Employer: Independent Contractor
::*2016 - Now
::*Responsibilities: Maintained Client Software and Infrastructure, connected clients with the technological solutions that would fit their businesses needs. Advised on a range of problems from cybersecurity, I.T., employee security training, SD-WAN, Cloud Compute Infrastructure, Disaster Recovery, Call Center As A Service, Unified Communications as a Service, and more.
: Business Development
::*Employer: Telecom Las Vegas
::*2021 - 2023
::*Tasked with maintaining communication with technological partners, onboarding firms that we engaged in partnerships with, maintaining critical company databases, and reformatting and transferring data to new systems.

===Personal Interest's and Hobbies===
My Top 3
#Physical Exercise
#Music Creation
#Outdoors Exploring in Nature
Additional Interest's and Hobbies
* Music Production
* Guitar
* Saxophone
* Biking
* Gym
* Surfing
* Soccer
* Bird (and Animal) Watching
* Painting
* Cooking (Especially Italian Food and Sushi)
* Construction & Fabrication
* Gaming
* Video Production
* Content Creation
* Reading
: Self-Teaching Guides (Examples)
::Self-Teaching Guide to Statistics
::Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks
: Textbooks in Free Time
:: Molecular Biology of the Cell Seventh Edition
:: Epigenetics, Second Edition
:: Introduction to Linear Algebra (Gilbert Strang, 5) 6th Edition
: Psychology Books
::
: Other Good Books
::Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science
::Stumbling on Happiness
::The Extended Selfish Gene
::Nudge: The Final Edition
::The Ten Commandments for Business Failure
::Thinking in Bets: Making Smarter Decisions When You Don't Have All the Facts
::[Zero to One] by [Peter Thiel], [Blake Masters] [September-16-2014]: [Notes on Startups], or [How to Build the Future] Paperback
:: The Innovator's Dilemma

: Books I need to get around to
:: Programming: Principles and Practice Using C++ (2nd Edition)
:: Understanding Digital Signal Processing

'''Favorite Aspect(s) of Biology'''
My favorite aspects of biology -at this point- are cell biology, genetics, systemic physiology, and Neurobiology. This is because I really want to work on tying all this together in a way that allows for the NON-GERMLINE modification of humans in a way that allows us to enhance our resistance to disease, treat disease, and enhance function, not necessarily all in my lifetime but it would be really awesome to help push this type of research forwards. Of course I strongly believe that all of this needs to be done carefully and with close adherence to rigorous standards and best practices.

'''Favorite Aspect of Computer Science'''
Right now my favorite aspect of computer science is AI. I think there is a huge amount of promise, but also a lot about it scares me. It makes me want to learn more. I have also been interested in how the brain works and how to make computers do tasks like the brain since pre-k. I just really like the simplicity of computer logic.

===Weekly Journals===

{{Template:Asandle1}}

===References===
Wikipedia page that shows how to use "wikitext". Which I used to help with formatting
[https://en.wikipedia.org/wiki/Help:Wikitext#:~:text=The%20markup%20language%20called%20wikitext,edit%2C%20see%20Help%3AEditing.| Click here]
Also a cheatsheet: [https://en.wikipedia.org/wiki/Help:Cheatsheet| Click here] which was a condensed version of the first wikipedia page.

In addition I found a great HTML resource which I may use, and If I use, I will add it to my bibliography.
[https://www.shecodes.io/athena/11906-centering-paragraphs-in-html-with-css#:~:text=To%20center%20a%20paragraph%20in%20HTML%2C%20you,use%20the%20tag.| Website for HTML Formatting]

===PDF To Test PDF's===
[[Media: Andrew_Sandler_Evil_Essay_Final_Draft.pdf | My freshman year essay on Evil]].

===Templates===

Individual Template

[[Template:Asandle1]]

Teammate Templates

[[Template:Andrew and Dean Journal 1]]

Blanks

[[Template: Andrew and Hailey]]

[[Category:Journal Entry]]

===Andrew Sandler's References===

Acknowledgements

I worked with''' 'Dean' '''Matthew Symonds on this shared journal assignment for about 2 hours.

- We met over FaceTime from 7:15 - 9:15

- We worked on the last bit of our user pages individually over FaceTime but offered suggestions and support.

- I gave him the 'code' for images, which I got from the wikipedia formatting page that is linked in the references at the bottom of my user page

- I used wiki syntax info from the same wikipedia page and the cheatsheet page which is also in the references on my user page.

- Used his LMU BioDB reference in my bibliography and Denning (2004) and Janovy (2007) that he made the APA citation for.

- All work is my own except where acknowledged otherwise [[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 12:19, 18 January 2024 (PST)

Bibliography

#LMU BioDB 2024. (2024). Week 1. Retrieved January 8, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/Spring2024/index.php/Week_1
#Janovy, J. (2004). On becoming a biologist. U of Nebraska Press.
#Denning, P. J. (2007). Computing is a natural science. Communications of the ACM, 50(7), 13-18.
#Denning, P. J. (2008). The profession of ITVoices of computing. Communications of the ACM, 51(8), 19–21. https://doi.org/10.1145/1378704.1378711

== Sandbox ==
To User Page: [[User: Asandle1]]

To Assignment Page: [[Week 2]]

Template:Asandle1

2024-04-30T16:37:57Z

Kdahlquist: remove shared category

To User Page: [[User: Asandle1]]
To Template: [[Template:Asandle1]]

====Assignment Pages====

[[week 1]]

[[week 2]]

[[week 3]]

[[week 4]]

[[week 5]]

[[week 6]]

[[week 7]]

[[week 8]]

[[week 9]]

[[week 10]]

[[week 11]]

[[week 12]]

[[week 13]]

[[week 14]]

[[week 15]]

====Journals====

=====Individual=====
[[User:Asandle1]]

[[Asandle1 Week 2]]

[[SIR2 Week 3]]

[[Monarch Initiative Week 4]]

[[Asandle1 Week 5]]

[[Asandle1 Week 6]]

[[Asandle1 Week 8]]

[[Asandle1 Week 9]]

[[Asandle1 Week 10]]

[[Asandle1 Week 12]]

[[Asandle1 Week 13]]

[[Asandle1 Week 14]]

[[Asandle1 Week 15]]

====Class Journals====
[[Class Journal Week 1]]

[[Class Journal Week 2]]

[[Class Journal Week 3]]

[[Class Journal Week 4]]

[[Class Journal Week 5]]

[[Class Journal Week 6]]

[[Class Journal Week 8]]

[[Class Journal Week 9]]

[[Class Journal Week 10]]

[[Class Journal Week 12]]

[[Category: Journal Entry]]

Template:Andrew and Hailey

2024-04-30T16:37:32Z

Kdahlquist: remove shared category

To User Page: [[User: Asandle1]], [[User: Hivanson]]

To Assignment Page: [[Week 2]]

===Andrew Sandler's Entry===

====Andrew Sandler's References====

=====Acknowledgements=====

- Used the first week's template with Dean to base this week's template on.

- All work is my own except where acknowledged otherwise [[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 21:32, 24 January 2024 (PST)

===== Bibliography =====

===Hailey's Entry===

====Hailey's Acknowledgements====

=====References=====

[[Category: Journal Entry]]

Template:Andrew and Dean Journal 1

2024-04-30T16:37:09Z

Kdahlquist: remove shared category

To User Page: [[User: Asandle1]], [[User: Msymonds1]]

To Assignment Page: [[Week 1]]

==Shared Entry==

===Andrew Sandler's Entry===

====Before Reading's====
'''Before Denning articles, answer the following questions'''

'''When you hear the term computer science, what comes to mind?'''

Hardware, software, the enigma machine, zeros and ones, binary, java, python, c++, compilers, electrical engineering, circuits, switches, algorithms, Artificial Intelligence, transformer architecture.

'''When older relatives or friends hear the term computer science, what do you think comes to their minds?'''

Punch cards, analog computers, enigma machine, huge mainframes.

'''When younger relatives or friends hear the term computer science, what do you think comes to their minds?'''

Video games, AI, newer languages

'''Before Reading the Janovy chapter (on your honor) answer the following questions'''

'''When you hear the term biology, what comes to mind?

Humans, Cells, DNA, Transcription

'''Do you consider yourself a *biologist*? why or why not?'''

Im interested in biology, but I don’t have the practical knowledge or experiences I would need to consider myself a biologist. (I read this article before answering these questions accidentally so I am trying to answer as if I hadn’t read the article, I did not read the Denning articles ahead of time though)

'''After Reading the Dennings Articles and the Janovy Chapter, answer the following questions:'''

'''What was the purpose of these readings?'''

To give us perspective on what we are doing in our course, dispel rumors and help us understand a fuller picture of what is out there and what we can gain and learn and take with us.

'''Which of the voices in the Voices of Computing article seem to appeal to you the most?'''

Honestly, not to say this as a cop out but I really liked all of them. I’m not really sure why I am saying this, but I like the Computational Programmer a lot. Its really a tough choice but I think about this one thing from the article on a daily basis where it said: “Perhaps my greatest triumph is to get people everywhere to think their brains are computers and that everything they do and say is simply an output. “

'''Apply one of the seven principles from the *Computing is a Natural Science* article to something as "non-computer-science"-y as possible, either from other subjects or your daily life.'''

I was reminded of a youtube video by Artem Kirsanev immediately called [[Place cells: How your brain creates maps of abstract spaces:www.youtube.com/watch?v=iV-EMA5g288&list=PLgtmMKe4spCMzkiVa4-eSHVk-N4SC8r9K&index=1]]

It sort of ties into computers already though. In terms of non-computer science, I immediately thought of strawberries, bananas, and nectarines —I really like fruit — and how they are each made up of individual parts (cells). I also think about bottlenecks in terms of my shower faucet, since it always seems to get really high in pressure but never has enough water coming out of it.

'''What did you find most interesting or provocative about the Janovy reading?'''

The Janovy Reading was my favorite, I took extensive notes because It really spoke to me. I actually texted my cousin the sentence in the article regarding doing and being, I do, I am. And the differences. This is probably one of my top 10 readings that Ive done in my college career.

'''What does it mean to be a biologist? Do you consider yourself a biologist? Why or why not?'''

Since I cheated a bit and accidentally read ahead, it is nice that either way I would have said no. Im naturally extremely curious and observant, but not necessarily about the same things described in the reading. I don’t seek out nature, but I do try and take notice.

====Andrew Sandler's References====

=====Acknowledgements=====

I worked with''' 'Dean' '''Matthew Symonds on this shared journal assignment for about 2 hours.

- We met over FaceTime from 7:15 - 9:15

- We worked on the last bit of our user pages individually over FaceTime but offered suggestions and support.

- I gave him the 'code' for images, which I got from the wikipedia formatting page that is linked in the references at the bottom of my user page

- I used wiki syntax info from the same wikipedia page and the cheatsheet page which is also in the references on my user page.

- Used his LMU BioDB reference in my bibliography and Denning (2004) and Janovy (2007) that he made the APA citation for.

- All work is my own except where acknowledged otherwise [[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 12:19, 18 January 2024 (PST)

===== Bibliography =====

#LMU BioDB 2024. (2024). Week 1. Retrieved January 8, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/Spring2024/index.php/Week_1
#Janovy, J. (2004). On becoming a biologist. U of Nebraska Press.
#Denning, P. J. (2007). Computing is a natural science. Communications of the ACM, 50(7), 13-18.
#Denning, P. J. (2008). The profession of ITVoices of computing. Communications of the ACM, 51(8), 19–21. https://doi.org/10.1145/1378704.1378711

[[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 15:22, 29 January 2024 (PST)

===Dean's Entry===
Before reading the Denning articles
#When I hear computer science, I think of lots of code on a computer screen that seems cryptic and basically in another language (because it essentially is). I do not understand much about computer science, nor do I know of the languages of coding.
#When older relatives hear the term computer science, they likely think of big tech companies like google or Microsoft, and they think of all of the work that goes into all of their products and software.
#When younger relatives hear the term computer science, they likely think of video games or animation, which are the kinds of things that they interact with in regards to computer science.
Before reading the Janovy chapter
#When I hear the term biology, I think of dissections of animals and their anatomy, although I understand that that relates to a more surface level study of biology whereas the field dives much deeper into the foundations of life.
#I do not necessarily consider myself a biologist, for I will graduate college with only a minor in the field. However I know that a minor does give me more of a background in the field than most people.
After Reading the Articles
#The Denning article titled "voices of computing"'s purpose was to give a summary for the different perspectives of the different concentrations and careers within the large field of computing. The purpose of the second Denning article called "Computing is a natural science" was to give insight into the current state of the field of computing. Considering that today many people regard it as a field that is quite different from the natural sciences such as Biology or Chemistry, but it makes the point that computing is not such a different field and it connects it to the other sciences in this reading. The purpose of the Janovy reading "On becoming a Biologist" was to provide an account of how he found himself and how he ended up becoming a biologist.
#The voice that appeals to me the most is the voice of the computational thinker, for I do find myself often looking for patterns or systematic ways of understanding the world, and attempting to apply them to everything, similar to how the computational thinker uses algorithms and problem solving skills.
#A principle from the "Computing is a natural science" article is locality or recollection. This can be applied to our daily lives when we see or hear something that is reminiscent of memory of ours. Such as hearing somebody say a certain phrase that somebody else said to us once in a different context.
#What I found interesting about the Janovy reading is the fact that it emphasizes that there is not just one way to becoming a biologist, for I have always considered it to mean that you have a degree in biology and usually a graduate degree as well.
#After reading the article I would consider being a biologist being a student who has participated in biology classes or biology labs. For this reason, I do consider myself a biologist.
[[User:Msymond1|Msymond1]] ([[User talk:Msymond1|talk]]) 21:22, 29 January 2024 (PST)

[[Category: Journal Entry]]

Class Journal Week 5

2024-04-30T16:33:57Z

Kdahlquist: add category shared

==[[User:Hivanson | Hailey]]==
*What are your initial reactions to hearing about this case?
It is crazy to put your name and career on the line to tell a big lie that would eventually be caught. Additionally, I was shocked that Dr. Potti was able to get away with lying about being a Rhodes scholar for as long as he did; it makes me wonder how many fraudulent resumes and CVs there are floating around that don't get a second glance.

Responding to [[User:Hivanson|Hailey]]: It is crazy to me. We talked about this sort of thing in my business ethics class and a lot of the class said they have lied on their resumes and don't think it is a problem, that it is almost a prerequisite to get a job, which I think is insane. [[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 19:57, 15 February 2024 (PST)

*What role did data sharing play in uncovering this fraud?
When data was analyzed to verify results, some findings were unable to be explained and errors were found. Had data not been shared, this external verification would not have been completed and the tumor-drug match program would have been investigated much later if at all.
As stated in the DataOne slides, data sharing can increase data quality with its inherent transparency. Data sharing proved to be critical in this real-world case.
*What additional information would you like to know about this case? (We will be visiting it again in subsequent weeks in the course.)
I'm curious how they claimed to be able to match each person's specific case to its proper drug. As we discussed in class on 2/13/2024, there are infinite genetic sequences, and to claim to be able to match that sequence to an ideal drug without having spent years collecting data and writing algorithms to match tumor to drug should raise more red flags than it seemed to have done. Though I haven't looked into it; maybe database building and writing a program was part of the study/claims.

[[User:Hivanson|Hivanson]] ([[User talk:Hivanson|talk]]) 23:14, 14 February 2024 (PST)

==Charlotte==
*What are your initial reactions to hearing about this case?

My initial reaction to this case was concern about the implications of of scientific misconduct. When researchers engage in behaviors like data manipulation and misrepresentation, it undermines the trustworthiness of scientific research. In fields like cancer therapy where accuracy is critical, the repercussions of misconduct can be very damaging. This worries me for cancer patients and those of us who believe in these scientific discoveries.

*What role did data sharing play in uncovering this fraud?

Data sharing played a key role in uncovering the fraud carried out at Duke University. By openly sharing data, researchers enable others to scrutinize and validate their findings independently. In this case, discrepancies in the shared data raised suspicions, leading to further investigation.

*What additional information would you like to know about this case?

What measures did Duke University and other institutions involved take to address the misconduct and prevent similar incidents from occurring in the future?

[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 19:54, 14 February 2024 (PST)
==Dean Symonds==
#My initial thoughts are that this is obviously frightening because doctors are people that we are supposed to trust more than anybody, and this is a case in which a doctor is prioritizing their own prestige and achievements over helping patients.
Comment for Dean: It is so frightening, I had a similar scenario happen to me which is why I think it's so important for everyone to have a basic scientific knowledge so they can question authority figures when their health is on the line. [[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 19:59, 15 February 2024 (PST)
#Data sharing played a crucial role. For if the other doctors did not have access to this data, they would possibly never have uncovered the fact that the data was fabricated. Data sharing can clearly lead to many different problems, but cases like these illustrate why it is necessary.
#What happened to Dr. Potti after the events of this case? Is he still a practicing doctor? Did his career end with this case? Is his reputation still affected by this case?
[[User:Msymond1|Msymond1]] ([[User talk:Msymond1|talk]]) 22:40, 14 February 2024 (PST)

==Katie Miller==
#What are your initial reactions to hearing about this case? I was shocked that so many people were deceived by Dr. Potti and that he was able to get away with this fraud for so long. If it wasn't him manipulating the data like he claims, I think it is incredibly irresponsible that this manipulation wasn't realized for several years. I'm also surprised that it was in the field of cancer research that this occurred, as there are so many people who are either impacted by cancer diagnoses or are involved in finding a cure. Dr. Potti was very bold to fabricate data in a field that has so many researchers, but it was likely the prestige of finding a cure like this one that caused him to manipulate his data.
#What role did data sharing play in uncovering this fraud? The data involved in this fraud was shared to several high profile databases that did not notice that they were receiving manipulated data. For many people who accessed his papers, they likely didn't consider that the data had been manipulated as it came from a reputable database. But, because the data was available to access, the fabricated data was eventually discovered and clinical trials were stopped, though this did take the trials being paused, resumed, and then finally stopped.
#What additional information would you like to know about this case? (We will be visiting it again in subsequent weeks in the course.) I would like to know if Potti ever faced legal repercussions for what he did, or if they even confirmed that it was him who had manipulated the data, as he claims it was not.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 23:33, 14 February 2024 (PST)

==Andrew Sandler==
Initial reactions and thoughts to hearing about this case:

*The intro could be an issue because 60 minutes is dumbing down the explanation for the average audience, but it mentions how somehow matching a chemo drug to a persons genetics could work. That doesn’t make sense since all types of cancerous cells have different mutations that led to them being cancerous. Just matching someone’s DNA would be the same as saying this person likes hot dogs and not hamburgers so we should use XYZ cancer therapy on them.
*It’s not the biggest medical fraud ever. There are frauds that entire disciplines were built on that we are only uncovering like the fraud in a major paper about Alzheimer’s.
*I pitched using AI to detect data fraud and inconsistencies to the LMU Startup Weekend and everyone thought the idea was stupid. I still think it would be paradigm shifting and highly lucrative.
*I dont know enough about cancer treatment but it sounds like the scientific community saw something that looked like a breakthrough but and a money maker. They took shortcuts and started working with patients way sooner than they should have. There were clearly a lot of forces driving this, and it is definitely something lots of people do in those situations on the business side. Sometimes it is important to slow down and be “fearful when others are greedy” and visa versa.
*It sounded like Duke was doing the right thing but i am confused how the committee could decide he was correct if he wasn’t.
*I feel bad for the people who were affected by this. And the manipulation of the data is disgusting.

What role did data sharing play in uncovering this fraud?

Data sharing was the only reason the fraud was uncovered. I worry what happens now where AI can quickly and easily fabricate data.

What additional information would you like to know about this case?

I want to understand how the independent investigative team duke hired didn’t see any issues with the data.

[[User:Asandle1|Asandle1]] ([[User talk:Asandle1|talk]]) 19:55, 15 February 2024 (PST)

==Natalija==
What are your initial reactions to hearing about this case?
*I was shocked and scared to see that a doctor would do something like this. Especially when they said that the drug could be harming them. Having cancer is scary enough, but then thinking that there is a drug that could help you, which in the end could cause you more harm is devastating. I'm surprised that Duke continued with the discovery even after there were alarming things being seen.
What role did data sharing play in uncovering this fraud?
*Data sharing played a big role in uncovering this fraud because without it the people would have not found errors in his findings. Ultimately, the data sharing saved lives because Dr. Potti manipulated the data and people were able to realize and see this despite the university and outside investigators not thinking anything is wrong.
What additional information would you like to know about this case? (We will be visiting it again in subsequent weeks in the course.)
*I would like to know what has been done to make sure this doesn't happen again. There were clearly so many issues yet people did nothing. I also want to know if Dr. Potti and the doctors/researchers involved are allowed to practice again because this seems like he knew what was happening.

[[Category:Shared]]

Yeast Beasts

2024-04-30T16:27:16Z

Kdahlquist: change Assignment category to Journal Entry

* This page will be the main place from which the Yeast Beasts team project will be managed. Include all of the information/links that you think will be useful for your team to organize your work and communicate with each other and with the instructors. ''Hint: the kinds of things that are on your own User pages and on the course Main page can be used as a guide.''

==Week Reflections==
===Week 13===
====[[User:Hivanson|Hailey's]] Reflection [Quality Assurance]====
*I worked closely with Charlotte and Katie toward completing Milestones 2 and 3. We completed milestone 2 and are close to completing milestone 3.
*I thought it worked well to split up, with Natalija going with the coder/designers and me going with data analysis, ''but'' I would love to see where they are at on their progress so that we can join up for the upcoming milestone 4. I want to do this on or before next Tuesday, April 30th.
*It did not work to try to do tasks simultaneously with the data analysts. To fix this, we had one person with an open Excel sheet on their computer, another reading and checking off the steps, and another checking that all of the data and equations were being entered properly. This solution worked well for us and we will continue to have just one computer with Excel open on it, but switching roles between the person inputting data and the one checking off steps could be better for the future.

[[User:Hivanson|Hivanson]] ([[User talk:Hivanson|talk]]) 23:35, 17 April 2024 (PDT)

====Andrew's Reflection [Coder/Designer]====
To find my electronic notebook for this week please click on [[Asandle1 Week 13#Electronic Lab Notebook|Andrew Sandler's Week 13 Lab Notebook]]
'''Executive Summary'''

#Classified Significant P-values as 1 (P < 0.01) or '0'
#Found issues with data including missing gene descriptions.
#Initially tried to use Yeastmine to find the missing gene information but it was inefficient.
#Found additional blanks in the dataset and need to speak with Dr. Dahlquist about how to solve this issue.

'''What worked?'''
Everything "worked" but some surprises came up.

'''What didn't work?'''
Not that this didn't work but it provided a challenge, the issues with the #REF boxes, the blank boxes, the random text in some boxes, and the NaN coming up in some spots. I don't know how to deal with this and will need help from Dr. Dahlquist so I am not just guessing at a solution. I also need to figure out how to get a complete Gene ID list and then compare the whole ID list to the missing ID's. I also need that list for the ID's for the Access Database.

'''What will I do next to fix what didn't work?'''
I plan on speaking with Dean and Dr. Dahlquist in class tomorrow to fix these issues and then move onto working on the Access section of this assignment.

[[Category:Journal Entry]]
[[Category:Team Project]]

====Dean's Reflection [Coder/Designer]====
# This week, me and my partner completed milestones 1 and 2, and we are currently working on milestone 3, there are some complications in milestone 3, for a large part of it requires Microsoft Access, and there are also some issues in importing tables to excel. [[MSymond1]]
# Each team member should reflect on the team's progress:
## The things that worked well are cleaning up the data for the network table, which was done in class on Tuesday, the data table looks much more organized and the p values have all been successfully converted
## The other data tables are not pasting into excel as neatly as anticipated, I am also unaware of how to obtain the data from the yeastmine website.
## To fix these issues, I will ask Dr. Dahlquist for further advice in class on Thursday.
[[User:Msymond1|Msymond1]] ([[User talk:Msymond1|talk]]) 13:33, 18 April 2024 (PDT)

====Katie's Reflection====
#This week, Charlotte, Hailey, and I worked on completing Milestones 2 and 3. These milestones consisted of preparing the dataset from SGD for analysis, and then performing an ANOVA analysis like we had done in Week 9. A more detailed summary of the steps we followed is outlined on mine and Charlotte's individual page, linked below.
#* [[Data Analysts Week 13]]
#The data analysts, me and Charlotte, worked together with Hailey on progressing through Milestones 2 and 3 on the Data Analysis page. We contacted each other throughout the week to check in on what each person was doing. We then met in person to work together on performing the ANOVA analysis. This worked well, because when we couldn't meet we were still able to get some work done, and then once we got together we were able to ask any questions that we had. It was slightly difficult to progress through the steps in person because when attempting to work on the dataset at the same time, only one person could be actively making changes. I don't believe it is possible for this issue to be fixed, as we cannot have multiple people working at exactly the same time, because steps need to be followed in a specific order. In the future, we will continue to make sure that we split up the steps so that each person is doing an equal amount of work, and to be communicative about any questions that we have or can answer.

[[User:Kmill104|Kmill104]] ([[User talk:Kmill104|talk]]) 23:09, 17 April 2024 (PDT)

====Charlotte's Reflection:====
[[User:Kmill104| Katherine Miller]] and I, being the data analysts, worked with Quality Assurance [[User:Hivanson| Hailey Ivanson]] to complete Milestone 2 and Milestone 3 in person on April 17th, 2024. We messaged the Coder/Designers and got an update from them. I wrote out the steps taken on our [[Data Analysts Week 13]] page. It was helpful that we were able to meet in person to collaborate. However, it was hard to make changes to the data since we were working on one computer. We ended up splitting up the work well, but at first everyone trying to make edits at once was hard. Now we know a system that works for us as a group.

[[User:Ckapla12|Ckapla12]] ([[User talk:Ckapla12|talk]]) 14:00, 18 April 2024 (PDT)

===Week 14===
===Week 15===
# Each person needs to write a short executive summary of that person's progress on the project for the week, with links to the relevant individual journal pages (which will have more detailed information).
# Each team member should reflect on the team's progress:
## What worked?
## What didn't work?
## What will I do next to fix what didn't work?
# Note that you will be directed to add specific information to your team's pages in the individual portion of the assignment for this and future weeks.

{{Yeast_Beasts}}
[[Template:Yeast_Beasts]]

Data Analysts Week 14

2024-04-30T16:24:54Z

Kdahlquist: add category

Data Analysts Week 13

2024-04-30T16:24:35Z

Kdahlquist: add category

Data Analysis

2024-04-26T16:53:10Z

Kdahlquist: /* Milestone 5: Create a candidate gene regulatory network and input workbook for GRNmap using MS Access database */ paste in instructions for database queries

{{Final Project Links}}

The role of the Data Analyst will be to apply the data analysis pipeline that you learned by analyzing the Dahlquist Lab microarray dataset to complete the analysis of a different published yeast timecourse microarray dataset. The Data Analysts are the end-users of the project, ultimately determining whether the work of the coder/designer and quality assurance members is useful to them.

== Guild Members ==

* Katie & Charlotte

== Milestones ==

The milestones do not necessarily correspond to particular days/weeks; instead they are sets of tasks grouped together.

* Data Analysts can have a shared ''individual'' journal entry. Both students will be given the same grade and are expected to contribute equally to the electronic lab notebook.
* Detailed notes should be taken throughout consistent with reproducible research and contributing to the final deliverables.

=== Milestone 1: Journal Club Presentation ===

* The Data Analysts will work with their teams to create and deliver a Journal Club presentation about to their team's assigned paper.

=== Milestone 2: Getting the data ready for analysis ===

# Download and examine the microarray dataset, comparing it to the samples and experiment described in your journal club article.
#* [https://sgd-prod-upload.s3.amazonaws.com/S000204389/Sha_2013_PMID_24073228.zip Link to processed dataset from SGD.]
#* For your reference, this is the link to the dataset at the GEO Database:[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26169 GSE26169]. However, we will use the dataset processed by SGD.
# Along with the QA's, make a "sample-data relationship table" that lists all of the samples (microarray chips), noting the treatment, time point, and replicate number.
#* Come up with consistent column headers that summarize this information
#** For example, the Dahlquist Lab microarray data used strain_LogFC_timepoint-replicate number, as in wt_LogFC_t15-1.
#** Do not use any special characters except for "-" or "_" (e.g., no commas, etc.)
# Organize the data in a worksheet in an Excel workbook so that:
#* ID (SGD systematic name) is in the first column
#* Data columns are to the right, in increasing chronological order, using the column header pattern you created
#* Treatments are grouped together
#* Replicates are grouped together
#* Delete the "EWEIGHT" row and "GWEIGHT" column.
# These data are from an Affymetrix, single-color chip. So, instead of ratios, the values are raw intensity values. We need to convert the data into Log2 fold changes (LogFC).
#* The raw intensity values have been log-transformed, which we need to undo before we calculate the ratios.
#* Create new column headers and then do the transformation of all the data with the equation <code>=2^<cell designation></code>
#* Compute the average value of the t0 timepoint for the control and CHP-treated data.
#* Calculate the fold change by dividing each value for each timepoint by the average t0 value for the respective treatment (control or CHP-treated).
#* Log2 transform the fold changes.
#* The data are now ready for the next step.

=== Milestone 3: ANOVA analysis ===

# Perform an ANOVA analysis of the data (including the Bonferroni and Benjamini and Hochberg corrections), as you did on [[Week 9]] for the Dahlquist lab data.
#* Perform the ANOVA separately for the Control vs. the CHP-treated data.
#* Note that you will need to adjust your formulas to take into account the different number of timepoints and replicates in your article's dataset.
# Perform a "Sanity Check" and create a table of p value counts like you did for the [[Week 9]] assignment. This time, do the Sanity Check on the Benjamini-Hochberg corrected p values instead of the unadjusted p values.
#* You will need to determine a suitable p-value cut-off for the clustering analysis. A suitable cut-off will include about 25% of the total number of genes.

=== Milestone 4: Clustering with stem and YEASTRACT ===

# Cluster the CHP-treated data with stem, as you did on [[Week 10]]. Collect the screenshots of the main clustering results and the plots of all significant clusters. What are the main patterns that you see? Are they similar to what was reported in the Sha et al. (2013) paper?
#* Note that we will make some adjustments to the GO term analysis because stem was not providing GO term names. We are going to use the GO enrichment tool at GeneOntology.org instead.
## Go to [http://geneontology.org/ http://geneontology.org/].
## Select two clusters with different patterns that have a reasonably large number of genes. For each cluster you want to analyze, open the gene list and copy the list of genes.
## Paste the list of genes into the "Go Enrichment Analysis" box on the right hand side of the GeneOntology.org page.
## Select "Saccharomyces cerevisiae" from the species drop-down menu.
## Click the "Launch" button.
## Near the bottom of the results page, click on the button to Export "Table".
## This will prompt you to save a .txt file that can be opened in Excel to view your results.
# Use YEASTRACT to generate a list of candidate regulatory transcription factors in [[Week 10]].

=== Milestone 5: Create a candidate gene regulatory network and input workbook for GRNmap using MS Access database ===

# Create an input workbook for GRNmap using queries to the Microsoft Access database that the Coder/Designer and QA's make. The main worksheets you will need to create are as follows:
#* <code>production_rates</code>
#* <code>degradation_rates</code>
#* <code>wt_log2_expression</code> (based on the CHP-treated data)
#* <code>network</code>
# Run GRNmap in Dr. Dahlquist's research lab (make appointment) and interpret data.
# As the end-user of the Access database, the Data Analysts will provide feedback to the QAs and Coder/Designer about the usability of database.

==== Using Microsoft Access Query Design ====

This is a loose set of instructions on how to use your Microsoft Access database to make the GRNmap input workbook.

# Import a table into the database that is the list of regulatory transcription factors that need to be included in the network (get from the Data Analysis team).
# Go to the Query Design view and select the tables that you need for the query. (For example, the TF table you just imported and the production_rates table).
# Link the ID fields that are equivalent.
# Right-click on the line between the fields and set the join properties:
#* Include all the records from the TF table, and only those records from the other table that match.
# Select the fields from the tables that you want to be output in the query and drag them to the grids at the bottom of the window.
# Choose "Make Table" query so that your results will be stored in a table.
# Run the query.
# Export the table created as tab-delimited text file. Bring it into Excel.
# Repeat as needed to create all of the worksheets you need.

{{Final Project Links}}

[[Category:Team Project]]

Quality Assurance

2024-04-26T16:52:37Z

Kdahlquist: /* Milestone 4: Validation, Quality Assurance, and Documentation of the Database */ paste in instructions for querying the access db

{{Final Project Links}}

The QA team member is the link between the Coder/Designer and the Data Analyst. He or she needs to know the details of the microarray dataset being analyzed so that the database being designed and populated by the Coder/Designer is correct and useful for the Data Analyst. The QA also makes sure that the data analysis steps are being performed correctly and are being correctly documented.

== Guild Members ==

* Hailey
* Natalija

== Milestones ==

The milestones do not necessarily correspond to particular weeks; instead they are sets of tasks grouped together.

* QA's can have a shared ''individual'' journal entry. Both students will be given the same grade and are expected to contribute equally to the electronic lab notebook.
* Detailed notes should be taken throughout consistent with reproducible research and contributing to the final deliverables.

=== Milestone 1: Journal Club Presentation ===

* The QA's will work with their teams to create and deliver a Journal Club presentation about to their team's assigned paper.

=== Milestone 2: Working with Data Analysts to understand microarray dataset ===

As an overview, the QA team members are the link between the Coder/Designer and the Data Analyst. He or she needs to know the details of the microarray dataset being analyzed so that the database being designed and populated by the Coder/Designer is correct and useful for the Data Analysts. The QA's will independently check that all of the data retrieved from SGD is present and accurately represented in the MS Access database. The QA will also provide assistance to the Data Analysts, making sure that the data analysis steps are being performed correctly and are being correctly documented.

# Download and examine the microarray dataset, comparing it to the samples and experiment described in your journal club article.
#* [https://sgd-prod-upload.s3.amazonaws.com/S000204389/Sha_2013_PMID_24073228.zip Link to processed dataset from SGD.]
#* For your reference, this is the link to the dataset at the GEO Database:[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26169 GSE26169]. However, we will use the dataset processed by SGD.
# Along with the QA's, make a "sample-data relationship table" that lists all of the samples (microarray chips), noting the treatment, time point, and replicate number.
# Report on these quality measures:
#* Are all the samples described in the paper in the dataset?
#* Are all the samples in the dataset described in the paper?
# Come up with consistent column headers that summarize this information
#* For example, the Dahlquist Lab microarray data used strain_LogFC_timepoint-replicate number, as in wt_LogFC_t15-1.
#* Do not use any special characters except for "-" or "_" (e.g., no commas, etc.)
# Organize the data in a worksheet in an Excel workbook so that:
#* ID (SGD systematic name) is in the first column
#* Data columns are to the right, in increasing chronological order, using the column header pattern you created
#* Treatments are grouped together
#* Replicates are grouped together
# This information needs to be relayed to the Coder/Designers so that they can design an appropriate <code>expression</code> table.

=== Milestone 3: Making sure expression data has both Sytematic Name and Standard Name ID's ===

* The design of the expression tables in the final database will need both an ID field (yeast systematic name) and Standard Name fields.
* You will need to check the IDs in the expression data and potentially populate one or both of these fields.
* One way to do this is use the [http://www.yeastract.com/formorftogene.php "ORF List <-> Gene List"] tool at YEASTRACT.
* The [http://llama.mshri.on.ca/synergizer/translate/ Synergizer] website may also be helpful.


=== Milestone 3: Design a database to store data needed to create a GRNmap input workbook ===

* Designer/Coders will work with the QA's to create a MS Access Database that will contain data needed to create a GRNmap input workbook.
** Databases created by the teams will be kept in a [https://lmu.box.com/s/lorqp5d5hkzqb7q161ldb66mhqfham3f "BIOL367_Spring2024" Box folder].
** Coder/Designer guild members have rights as editor to this folder; all others in the class can only view/download.
** This folder will serve as as the version control mechanism for the Coder/Designer guild.
* The database will need to have the following tables:
** A <code>gene</code> table that contains all of the gene IDs for the entire yeast genome, obtained from [https://yeastmine.yeastgenome.org/yeastmine/begin.do YeastMine].
** An <code>expression</code> table to store the yeast time-course microarray data for the dataset being analyzed by the Data Analysts. You will consult with the Data Analysts and QA's to figure out the sample-data relationships and how that should be encoded as fields in the database.
** A <code>degradation_rates</code> table that contains degradation rates from Neymotin et al. (2014). This table will be provided.
** A <code>production_rates</code> table that contains initial guesses for the production rates for each gene. This table will be provided.
** A <code>network</code> table that contains the gene regulatory network data from the Harbison et al. (2004) paper.
** A <code>metadata</code> table that encodes information about the database itself, i.e., other tables in the database.
*** A major part of the design work will be to figure out what information needs to be in the metadata table so that queries can be easily and uniquely performed on the data.

=== Milestone 4: Validation, Quality Assurance, and Documentation of the Database ===

* The QA will perform quality assurance to make sure that the database is correct and accurate.
** In particular, the QA's need to make sure that all of the rows of data were imported into the database for each table.
** The QA's will make sure that both the ID (SGD systematic name) and Standard Names are included in the expression table and are correct.
* QA's will collect feedback from the Data Analysts and communicate to the Coder/Designers any changes needed to the database.
* With the QA's finalize the [https://www.quackit.com/microsoft_access/microsoft_access_2016/howto/how_to_create_a_database_diagram_in_access_2016.cfm database schema diagram]

==== Using Microsoft Access Query Design ====

This is a loose set of instructions on how to use your Microsoft Access database to make the GRNmap input workbook.

# Import a table into the database that is the list of regulatory transcription factors that need to be included in the network (get from the Data Analysis team).
# Go to the Query Design view and select the tables that you need for the query. (For example, the TF table you just imported and the production_rates table).
# Link the ID fields that are equivalent.
# Right-click on the line between the fields and set the join properties:
#* Include all the records from the TF table, and only those records from the other table that match.
# Select the fields from the tables that you want to be output in the query and drag them to the grids at the bottom of the window.
# Choose "Make Table" query so that your results will be stored in a table.
# Run the query.
# Export the table created as tab-delimited text file. Bring it into Excel.
# Repeat as needed to create all of the worksheets you need.

{{Final Project Links}}

[[Category:Team Project]]

Coder/Designer

2024-04-26T16:51:52Z

Kdahlquist: /* Using Microsoft Access Query Design */ add instructions for query.

{{Final Project Links}}

The Coder/Designers are responsible for creating the Microsoft Access database that will be used by the Data Analysts to prepare an input workbook for GRNmap for the microarray dataset they are analyzing. The Coder/Designers are also the resident experts on the technology being used—assorted software, file management, version control, and troubleshooting. He or she coordinates with Dr. Dahlquist and fellow Coders/Designers in developing the Access database and storing it on Box.

== Guild Members ==

* Dean
* Andrew

== Milestones ==

The milestones do not necessarily correspond to particular weeks; instead they are sets of tasks grouped together. However, Milestone 3 is a hard prerequisite for proceeding to Milestone 4, so ideally the Coder/Coder guild should finish these milestones (they require some coordination; see below) as soon as possible.

* Coder/Designers can have a shared ''individual'' journal entry. Both students will be given the same grade and are expected to contribute equally to the electronic lab notebook.
* Detailed notes should be taken throughout consistent with reproducible research and contributing to the final deliverables.

=== Milestone 1: Journal Club Presentation ===

* The Coder/Designers will work with one of the QA's to create and deliver a Journal Club presentation about to their assigned paper.

=== Milestone 2: Working Environment Setup ===

Coder/Designer work will require the following software/accounts. The Seaver 120 lab computers are already set up for this; this list is provided for Coders/Designers who need to work on a different computer or outside of the lab.
* Microsoft Access
* Box account (provided by LMU)
** Databases created by the teams will be kept in a [https://lmu.box.com/s/lorqp5d5hkzqb7q161ldb66mhqfham3f "BIOL367_Spring2024" Box folder].
** Coder/Designer guild members have rights as editor to this folder; all others in the class can only view/download.
** This folder will serve as as the version control mechanism for the Coder/Designer guild.

=== Milestone 3: Design a database to store data needed to create a GRNmap input workbook ===

* Designer/Coders will work with the QA's to create a MS Access Database that will contain data needed to create a GRNmap input workbook. It will need to have the following tables:
** A <code>gene</code> table that contains all of the gene IDs for the entire yeast genome, obtained from [https://yeastmine.yeastgenome.org/yeastmine/begin.do YeastMine].
** An <code>expression</code> table to store the yeast time-course microarray data for the dataset being analyzed by the Data Analysts. You will consult with the Data Analysts and QA's to figure out the sample-data relationships and how that should be encoded as fields in the database.
** A <code>degradation_rates</code> table that contains degradation rates from Neymotin et al. (2014). This table is provided at [[Media:Degradation_rates.txt| this link]].
** A <code>production_rates</code> table that contains initial guesses for the production rates for each gene. This table is provided at [[Media:Production_rates.txt | this link]].
** A <code>network</code> table that contains the gene regulatory network data from the Harbison et al. (2004) paper. [[Media:Pvalbygene_forpaper_abbr.xls | Here is the link to the data.]]
** A <code>metadata</code> table that encodes information about the database itself, i.e., other tables in the database.
*** A major part of the design work will be to figure out what information needs to be in the metadata table so that queries can be easily and uniquely performed on the data.

=== Milestone 4: Build the database ===

* Once the design work has been completed, you need to actually import the data into the database.

=== Milestone 5: Validation, Quality Assurance, and Documentation of the Database ===

* The QA will perform quality assurance to make sure that the database is correct and accurate.
** In particular, the QA's need to make sure that all of the rows of data were imported into the database for each table.
** The QA's will make sure that both the ID (SGD systematic name) and Standard Names are included in the expression table and are correct.
* QA's will communicate to the Coder/Designers any changes needed to the database.
* With the QA's finalize the [https://www.quackit.com/microsoft_access/microsoft_access_2016/howto/how_to_create_a_database_diagram_in_access_2016.cfm database schema diagram]

=== Milestone 6: Document the schema and design queries to create the GRNmap input workbook ===

* Assist the Data Analysts with the queries needed to creat a GRNmap input workbook
* This is a sample of a GRNmap input workbook: [[Media:15-genes_28-edges_sample-GRNmap_Sigmoid_estimation.xlsx | 15-genes_28-edges_sample-GRNmap_Sigmoid_estimation.xlsx]]
** '''''Note that you will need to match the column ids and worksheet names exactly, including case. The worksheets need to be in the exact order of the sample workbook as well.'''''
* This is a description of what needs to go into each worksheet:
** <code>production_rates</code>: two columns
*** <code>id</code>: standard names of the genes encoding the regulatory transcription factors in the network, in alphabetical order
*** <code>production_rate</code>: mRNA production rates for each of the genes
** <code>degradation_rates</code>
*** <code>id</code>: standard names of the genes encoding the regulatory transcription factors in the network, in alphabetical order
*** <code>degradation_rate</code>: mRNA production rates for each of the genes
** <code>wt_log2_expression</code>
*** <code>id</code>: standard names of the genes encoding the regulatory transcription factors in the network, in alphabetical order
*** Log2 fold changes for each gene for all the timepoints and replicates to be included in the analysis. The timepoints should be arranged in chronological order with the replicates grouped. The column headers are the time in minutes (just the number). See the sample for how it should be arranged.
** <code>network</code>
*** Cell A1 needs to have <code>cols regulators/rows targets</code>
*** This is an adjacency matrix encoding the network connections. All genes to be included in the network should appear in column 1 and row 1 in alphabetical order.
*** A "0" indicates no connection between them.
*** A "1" indicates that the transcription factor in the column regulates the corresponding transcription factor in the row.
** <code>network_weights</code>
*** This sheet should be identical to the <code>network</code> sheet. It represents the initial guesses for the weight values for the modeling.
** <code>optimization_parameters</code>: this worksheet contains information needed for Matlab to run the model. This sheet should be copied from the sample and only two lines need to be modified:
*** <code>expression_timepoints</code>: this row should list the expression timepoints corresponding to the timepoints in the <code>wt_log2_expression</code> worksheet.
*** <code>simulation_timepoints</code>: this row is a list of timepoints that the model will simulate from the estimated parameters. It should begin and end with the same timepoint, but the intervals between the timepoints should be shorter than the experimental expression data.
** <code>threshold_b</code>: two columns
*** <code>id</code>: standard names of the genes encoding the regulatory transcription factors in the network, in alphabetical order
*** <code>threshold_b</code>: all 0. This represents the initial guesses for the threshold b parameter in the network.

==== Using Microsoft Access Query Design ====

This is a loose set of instructions on how to use your Microsoft Access database to make the GRNmap input workbook.

# Import a table into the database that is the list of regulatory transcription factors that need to be included in the network (get from the Data Analysis team).
# Go to the Query Design view and select the tables that you need for the query. (For example, the TF table you just imported and the production_rates table).
# Link the ID fields that are equivalent.
# Right-click on the line between the fields and set the join properties:
#* Include all the records from the TF table, and only those records from the other table that match.
# Select the fields from the tables that you want to be output in the query and drag them to the grids at the bottom of the window.
# Choose "Make Table" query so that your results will be stored in a table.
# Run the query.
# Export the table created as tab-delimited text file. Bring it into Excel.
# Repeat as needed to create all of the worksheets you need.

{{Final Project Links}}

[[Category:Team Project]]

Coder/Designer

2024-04-26T16:46:11Z

Kdahlquist: /* Milestone 6: Document the schema and design queries to create the GRNmap input workbook */ add section for query design

Main Page

2024-04-25T21:20:43Z

Kdahlquist: /* Materials (must be brought to each class meeting) */ comment out GitHub account

__NOTOC__
<div style="text-align: center; font-size: 175%">Loyola Marymount University</div>
<div style="text-align: center; font-size: 250%; line-height: 1.25em">'''BIOL 367-01: Biological Databases'''</div>
<div style="text-align: center; font-size: 175%; margin-bottom: 0.85em">Spring 2024</div>

<div style="float: right;">__TOC__</div>

== Announcements ==

* Don't forget to sign your class journal entries with your wiki signature! '''<nowiki>~~~~</nowiki>'''

=== Upcoming Seminars ===

''There are no more seminars for the remainder of the semester.''



== Instructor ==
* [[User:Kdahlquist|Kam D. Dahlquist]]

== Students ==

{| style="margin-left: auto; margin-right: auto"
| style="padding-right: 1em" | [[User:Hivanson| Hailey Ivanson]]
| style="padding-right: 1em" | [[User:Asandle1| Andrew Sandler]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Ckapla12| Charlotte Kaplan]]
| style="padding-right: 1em" | [[User:Nstojan1| Natalija Stojanovic]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Kmill104| Katherine Miller]]
| style="padding-right: 1em" | [[User:Msymond1| Dean Symonds]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|}

{{Final Project Links}}

== Schedule ==

The current course schedule is shown below. In addition to the listed in-class agendas, the following guidelines are also notable:

* Unless otherwise stated on the schedule, your weekly journals/assignments are due on Thursdays at 12:01am. In cases where subsequent revisions or corrections will be accepted, the instructor will provide feedback and submission deadlines on a per-assignment basis.
* Reading assignments should be completed ''before'' coming to class.

{| class="wikitable"
|-
! Week 
! Date 
! Before Class Reading 
! During Class Topic
! After Class Assignment
|- style="vertical-align:bottom;"
| rowspan="2" | 1
| 9-Jan
| 
|
* Syllabus walkthrough
* Pairwise interviews and introductions
* Academic Honesty case studies
* Wiki account setup
| rowspan="2" | [[Week 1]] (due 12:01am 1/18) [[Class Journal Week 1]] 
|- style="vertical-align:bottom;"
| 11-Jan
| [https://peerj.com/preprints/3215v1/ Dahlquist et al. (2017) ''An Invitation to Modeling'']
|
* What is a model?
* Model of a cell/model of a computer 
|- style="vertical-align:bottom;"
| rowspan="2" | 2
| 16-Jan
|
* Denning [http://dl.acm.org/ft_gateway.cfm?id=1378711 ''Voices of Computing''], [http://dl.acm.org/ft_gateway.cfm?id=1272529 ''Computing is a Natural Science''] (also available on [http://brightspace.lmu.edu/ Brightspace]).
* Janovy ''On Becoming a Biologist'' Chapter 1, available on [http://brightspace.lmu.edu/ Brightspace].
* Note that there are some ''before'' questions you should answer before completing these readings. See [[Week 1]].
|
* Discuss the Week 1 assignment
** Wiki syntax overview
** Lab session to setup User wiki page 
| rowspan="2" | [[Week 2]] (due 12:01am 1/25) [[Class Journal Week 2]] 
|- style="vertical-align:bottom;"
| 18-Jan
|
* [http://www.ncbi.nlm.nih.gov/books/NBK21134/#A5234 Brown, T.A. (2002) Ch. 1 ''Genomes 2'']
* [http://www.ncbi.nlm.nih.gov/books/NBK21121/ Brown, T.A. (2002) ''Genomes 2'', Ch. 3, especially section 3.3.2]
| DNA structure
|- style="vertical-align:bottom;"
| rowspan="2" | 3
| 23-Jan
|
* On [http://brightspace.lmu.edu Brightspace]:
** [https://www.sciencedirect.com/science/article/pii/S0968000403003025 Nirenberg (2004) ''Deciphering the Genetic Code'']
** [https://www.cell.com/trends/biochemical-sciences/fulltext/S0968-0004(04)00083-0 Kaji & Kaji (2004) ''Setting the Record Straight'']
** Moody (2004) ''Digital Code of Life'', Ch. 1
** Hayes (2004) ''Ode to the Code''
| Aipotu work session
| rowspan="2" | [[Week 3]] (due 12:01am 2/1) [[Class Journal Week 3]] 
|- style="vertical-align:bottom;"
| 25-Jan
| 
|
* Genes as models
* Central model of molecular biology
** [http://www.youtube.com/watch?v=u9dhO0iCLww Berkeley translation video]
** This [https://dnalc.cshl.edu/resources/animations/ web site] has links to animations of the replication, transcription, and translation processes.
** [http://brightspace.lmu.edu Slides on Brightspace]
* [[Media:BIOL367_Spring2024_GeneticCode-CentralModel.pdf | Paper and pencil exercise]]

|- style="vertical-align:bottom;"
| rowspan="2" | 4
| 30-Jan
|
* [http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/ Ford, Paul. “What is Code?” ''Business Week'', June 11, 2015.]
* [[Media:L01_DataManagement.pptx | DataONE: Data Management Slides]]
|
Introduction to biological databases ([[Media:2024-01-30_biological-databases-part1.pdf | part 1 slides]]) 
* What is bioinformatics?
* Open Science Ecosystem
* DataONE: Data management and the life cycle of data
* Terminology, types, four "Gold Standard" databases
| rowspan="2" | [[Week 4]] (due 12:01am 2/8) [[Class Journal Week 4]] 
|- style="vertical-align:bottom;"
| 1-Feb
|
* [[Media:L02_DataSharing.pptx | DataONE: Data Sharing Slides]]
* [https://doi.org/10.1093/nar/gkad1173 Rigden & Fernández (2024) ''NAR'' Database Issue editorial]
|
Introduction to biological databases ([[Media:2024-02-01_biological-databases-part2.pdf | part 2 slides]]) 
* A closer look at evaluating biological databases
* DataONE: Data sharing
|- style="vertical-align:bottom;"
| rowspan="2" | 5
| 6-Feb
| 
|
* Presentation Guidelines ([https://brightspace.lmu.edu .pptx is on Brightspace])
* Week 4 work session 
| rowspan="2" | [[Week 5]] (due 12:01am 2/15) [[Class Journal Week 5]] 
|- style="vertical-align:bottom;"
| 8-Feb
| 
|
Database presentations
* [[Media:Nemo_presentation.pdf | NeMO by Hailey & Dean]]
* [https://docs.google.com/presentation/d/1C74eHcvpTo0rnbQFcUnDsmG_AIPpIqLvM0t-DV95Obk/edit#slide=id.g1f0192797b8_0_30 Monarch Initiative by Katie & Andrew]
* [[Media:The_AgeAnnoMo_Database.pdf | AgeAnnoMO by Charlotte & Natalija]]

|- style="vertical-align:bottom;"
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 2: Going Deeper (Gene Expression Data and Relational Databases)'''
|-
| rowspan="2" | 6
| 13-Feb
|
* Moody (2004) ''Digital Code of Life'', Ch. 6 (on [https://brightspace.lmu.edu Brightspace])
* Original (2001) Human Genome Project articles in [https://www.nature.com/nature/volumes/409/issues/6822 ''Nature''] & [https://www.science.org/toc/science/291/5507 ''Science'']
* Special issues (2021) "The Human Genome at 20" in [https://www.nature.com/collections/febigehfbg ''Nature''] & [https://www.science.org/toc/science/371/6529 ''Science'']
| Human Genome Project
| rowspan="2" | [[Week 6]] (due 12:01am 2/22) [[Class Journal Week 6]] 
|- style="vertical-align:bottom;"
| 15-Feb
|
|
Where's my Stuff?
* Slides are on Brightspace
* An overview of computers, networks, files, web applications, web services, and databases
* Names, URLs, identifiers
** As applied to biology: genes, species
* “Stuff” on the worldwide web
** Accessing the web on a browser
|- style="vertical-align:bottom;"
| rowspan="2" | 7
| 20-Feb
| 
| [[Week 6]] work session
* Please bring ear buds/headphones if possible.

| rowspan="2" | No Week 7 Assignment
|- style="vertical-align:bottom;"
| 22-Feb
|
* [http://www.ncbi.nlm.nih.gov/books/NBK26818/#A1633 Alberts ''et al''. (2002) ''Molecular Biology of the Cell'', Ch. 8: Microarrays]
* [https://www.youtube.com/watch?v=0ATUjAxNf6U Microarray animation]
* [https://doi.org/10.1038/4462 Brown. & Botstein (1999)]
* Campbell, A.M. and Heyer, L.J. (2003), Ch 4 ([http://brightspace.lmu.edu on Brightspace])
* [https://doi.org/10.1126/science.278.5338.680 DeRisi, et al. (1997)]
| 'omics analysis
|- style="vertical-align:bottom; background-color:#e5fee8;"
| rowspan="2" | Spring Break
| 27-Feb
| rowspan="2" colspan="3" | No class
|- style="vertical-align:bottom; background-color:#e5fee8;"
| 29-Feb
|- style="vertical-align:bottom;"
| rowspan="2" | 8
| 5-Mar
|
* [https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf Ted Codd’s seminal paper “A Relational Model of Data for Large Shared Data Banks”]
* [https://dondi.lmu.build/share/db/super-basic-database-diagramming.pdf Super basic relational database concepts]
| Guest lecture: Dr. Dionisio
* Relational Databases part 1
| rowspan="2" | [[Week 8]] (due 12:01am 3/14) [[Class Journal Week 8]] 
|- style="vertical-align:bottom;"
| 7-Mar
| [https://dondi.lmu.build/share/db/super-basic-sql.pdf Super basic SQL crib sheet]
| Guest lecture: Dr. Dionisio
* Relational Databases part 2
|- style="vertical-align:bottom;"
| rowspan="2" | 9
| 12-Mar
| 
| [[Week 8]] work session 
| rowspan="2" | [[Week 9]] (due 12:01am 3/21) [[Class Journal Week 9]] 
|- style="vertical-align:bottom;"
| 14-Mar
| 
| Transcriptomic analysis (part 1)
* ANOVA
|- style="vertical-align:bottom;"
| rowspan="2" | 10
| 19-Mar
| [https://xkcd.com/882/ "Significant"]
| Transcriptomic analysis (part 2)
* Multiple testing problem, p value corrections
| rowspan="2" | [[Week 10]] (due 12:01am 4/4, interim deadlines on 3/26 and 4/2) [[Class Journal Week 10]] 
|- style="vertical-align:bottom;"
| 21-Mar
|
* [https://academic.oup.com/bioinformatics/article/21/suppl_1/i159/203147 Ernst, J., & Bar-Joseph, Z. (2006). STEM]
* [https://doi.org/10.1038/75556 Ashburner et al. (2000). Gene Ontology]
| Transcriptomic analysis (part 3)
* Clustering and GO term enrichment analysis
|- style="vertical-align:bottom;"
| 11
| 26-Mar
|
* [https://doi.org/10.1093/nar/gkac1041 Teixeira, et al. (2023) YEASTRACT+]
* [https://link.springer.com/article/10.1007/s11538-015-0092-6 Dahlquist et al. (2015) GRNmap]
* [https://peerj.com/articles/cs-85/ Dahlquist et al. (2016) GRNsight]
|
* Transcriptomic analysis (part 4)
** GRN modeling and visualization
| rowspan="2" | Continue with [[Week 10]] assignment
|- style="vertical-align:bottom; background-color:#e5fee8;"
| Easter
| 28-Mar
| colspan="2" | No class
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 3: Integrating for Research (GRNsight Gene Expression Database Project)'''
|-
|- style="vertical-align:bottom;"
| rowspan="2" | 12
| 2-Apr
| 
| Discussion of [[Week 10]] results
| rowspan="2" | [[Week 12]] (due 12:01am 4/11) 
|- style="vertical-align:bottom;"
| 4-Apr
| 
| Begin Database Project
* Overview of project
* Work session for journal club
|- style="vertical-align:bottom;"
| rowspan="2" | 13
| 9-Apr
| 
| Work session for journal club
| rowspan="2" | [[Week 13]] (due 12:01am 4/18) 
|- style="vertical-align:bottom;"
| 11-Apr
| 
|
* Journal Club Presentations
* Work session to organize milestones
|- style="vertical-align:bottom;"
| rowspan="2" | 14
| 16-Jan
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 14]] (due 12:01am 4/25) 
|- style="vertical-align:bottom;"
| 18-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom;"
| rowspan="2" | 15
| 23-Apr
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 15]] (due 12:00 noon 5/3) 
|- style="vertical-align:bottom;"
| 25-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom; background-color:#ffccc9;"
| rowspan="2" | Finals
| 2-May
|
| '''Final Presentations 11:00am''' 
| rowspan="2" |
|- style="vertical-align:bottom; background-color:#ffccc9;"
| 3-May
|
| '''Project Deliverables Due 12:00 noon''' 
|}

== Course Information ==

=== Instructor ===

==== [[User:Kdahlquist | Kam D. Dahlquist, Ph.D.]] ====
: http://kdahlquist.github.io/DahlquistLab/index.htm
: '''Phone:''' (310) 338-7697
: '''E-mail:''' kdahlquist at lmu dot edu
: '''Office:''' Life Sciences Building 289
: '''Office Hours (Spring 2024):''' Mondays 2:00-3:30 PM, Tuesdays 3:15-4:45, and by appointment; check [https://brightspace.lmu.edu Brightspace] for a Calendly link to make an appointment for a Zoom or in-person meeting.

=== Prerequisites/Recommended Background ===

BIOL 201 and MATH 123 or MATH 132 or MATH 204 or MATH 205.

=== Class Meetings and Attendance ===
TR 1:45-3:00pm, Seaver 120 

This is a hands-on, participatory course, thus attendance at all class meetings is required. Each student is allowed two “sick” days (automatically excused absences) during the semester. Further unexcused absences from class will result in a 12 point (2.5%) deduction from the overall course grade for each absence. Every effort should be made to attend class on oral presentation days as the content of that day's class is dependent on student participation. Unexcused absences from an oral presentation will result in a grade of zero for the presentation. The instructor should be notified as soon as possible, electronically or by phone, of the reasons for all absences.

Note that the last day to add or drop a class without a grade of W is January 12. The withdrawal or credit/no-credit status deadline is April 5.

=== Mutual Responsibilities ===

This course is designed to foster your development as a biologist and computer scientist and to give you an authentic research experience. We will be engaged together in discovering, examining, and practicing the personal qualities, technical skills, and community standards of the scientific community. While you are ultimately responsible for your own learning, you are not alone. Our class constitutes a team where we will be learning from each other. The role of the instructor is to provide the expert coaching to support and assist you on your journey. All of the exercises, readings, assignments, and policies detailed below have been designed with this purpose in mind.

=== Classroom Conduct ===

We are all responsible for maintaining a classroom and laboratory environment that is safe and conducive to learning. As such, we will observe the following:

# As an LMU Lion, by the [http://studentaffairs.lmu.edu/wellness/lmucares/aboutlmucares/livethelionscode/ Lion’s code], you are pledged to join the discourse of the academy with honesty of voice and integrity of scholarship and to show respect for staff, professors, and other students.
# You are responsible for your own learning and for being a good class citizen.
# Class will start promptly on time.
# You are expected to come to class having done the assigned reading and preparatory work so that you are ready to participate in discussions and to perform the laboratory exercises.
# You are expected to bring the required materials to each class session.
# Cell phones and other ancillary devices must be turned off and put away out of sight. Your own laptop and/or tablet may be used to conduct the class exercises, '''''provided that you have confirmed with the instructor that you have the correct versions of software installed for the exercise'''''. If, however, the laptops/tablets are being used for other purposes and become distracting to you or others, you will be asked to put them away.
# All students are governed by the [https://lmu.box.com/s/urox7s2vkxtoofg0rmmnv5h7ik5rahof Student Conduct Code]. Disruptive behavior which is persistent or significantly interferes with classroom activities may be subject to disciplinary action. A student may be referred to the Office of Student Judicial Affairs if his or her behavior constitutes a violation of the conduct code.

=== Course Website ===

This is the course web site and wiki, hosted by http://xmlpipedb.cs.lmu.edu/biodb/spring2024/. You will need to have a user account on this wiki to be able to edit the wiki and complete coursework. Updates to the course schedule and electronic copies of all handouts, assignments, and readings will be posted to this site. You will also use the site to keep an electronic lab notebook/journal for the course. In addition, students have been automatically enrolled in the course page on [http://brightspace.lmu.edu Brightspace]. The site will be used for materials that cannot be made public on this wiki, including grades.

=== Email Communication ===

At times I will communicate with the entire class using campus email systems, so it is essential that you regularly check your lion.lmu.edu email address or forward your lion account email to your preferred email address. Messages sent to the instructor at night or on the weekend will be answered the next school day.

=== Required Materials ===

==== Texts ====

There is no required text to purchase for the course; materials will be put on reserve at Hannon Library or will be available online on this wiki or [http://brightspace.lmu.edu Brightspace] site. Specific reading assignments are given on the course schedule and should be completed before coming to class.
* Assorted handouts, articles, and sample code will be distributed throughout the semester.
* Additional information is also available on the web; do not hesitate to look for further sources of information regarding the concepts, techniques, tools, and paradigms that we will discuss.

==== Materials (must be brought to each class meeting) ====

* 3-ring binder or folder with all course handouts
* Pen, pencil, extra paper
* USB flash drive to back-up data
* Account for this wiki


=== Course Description ===

The disciplines of biology and computer science come together in bioinformatics, where computational tools are needed to manage and analyze the flood of data coming from new genomics technologies. Biological databases form a significant part of this young and exciting field. This course introduces students to both the biology and computer science expertise needed to understand, use, and develop biological databases. Biology topics include the fundamentals of genetics, molecular biology, and biochemistry needed to understand the data stored in biological databases, as well as the biotechnologies used to gather these data in a high-throughput manner. Computer science topics include what biological databases are, why they are important (and needed), and the challenges that arise in compiling them effectively. Biology and computer science lectures on topics that are relevant to biological databases are coupled with hands-on experience with a variety of software packages ranging from bioinformatics utilities to general-purpose database and software development tools. After learning how to use a biological database, students will be asked to build one of their own.

==== Course Objectives and Learning Outcomes ====

This course is built upon L. Dee Fink’s ''taxonomy of significant learning'', as applied to biological databases. Long after the course concludes, our hope is that:
* You understand how biological information is encoded in the genome and can apply this knowledge to a variety of biological tasks and problems
* You understand the core concepts, structure, and functions of a database, ranging from individual files to a full relational database management system, and can perform useful tasks with such data
* You show discipline and proficiency in day-to-day science and engineering best practices, such as maintaining journals and notebooks, managing your files and code, and critically evaluating scientific and technical information
* You recognize and care about how the biological and technological issues presented in this course relate to and affect society, our daily lives, and ourselves
* You have some skills and tools for “leaving your comfort zone,” flourishing outside of it, and learning more about biology and computer science on your own
* You learn how to communicate and work effectively with colleagues from your discipline and different disciplines

==== University Core Curriculum ====

This course fulfills the following requirements in the University Core Curriculum:
* Integrations: Interdisciplinary Connections

=== Course Work and Grading ===

Your work in this course will be assessed in the following areas:

{| style="border: 1px dashed rgb(47, 111, 171); background: rgb(249, 249, 249); margin: 1em 0; padding: 1em" cellpadding="5ex"
| Weekly electronic lab notebook/journal assignments, individual (usually 12 points each)
| style="text-align: right" | 168 
| points
|-
| Weekly electronic lab notebook/journal assignments, shared (usually 3 points each)
| style="text-align: right" | 42 
| points
|-
| Oral presentations (3 @ 35, 45, 60 points)
| style="text-align: right" | 140
| points 
|-
| Final Project Deliverables (including written report)
| style="text-align: right" | 100
| points
|-
| '''Total'''
| style="text-align: right" | '''450''' 
| '''points'''
|}

Final course grading scale:
94.0-100.0% A
90.0- 93.9% A-
86.0- 89.9% B+
82.0- 85.9% B
78.0- 81.9% B-
74.0- 77.9% C+
70.0- 73.9% C
67.0- 69.9% C-
60.0- 66.9% D
≤ 59.9% F

Current grades will be made available at [http://brightspace.lmu.edu Brightspace].

==== Electronic Laboratory Notebook/Journal ====

One of the most important skills you can develop as a scientist is keeping an excellent laboratory notebook. For computational research, the equivalent of the biology paper-based lab notebook is documentation of your “workflow.” For this course you will practice documentation skills by keeping an electronic lab notebook or journal. The technology we will use is this wiki that we will create and edit during the semester. The wiki software is the same one that runs Wikipedia and many other wiki sites, so proficiency gained here is easily transferable to other applications.

You will create an individual user page and make weekly entries that the instructor will read and grade. You will use the wiki to complete the assignments as well. The following guidelines apply:
* Your weekly journal entry is typically due every 12:01am on Thursday Pacific time; consult the schedule for specific due dates for each assignment.
* Each weekly assignment has an individual component and a shared component. You will earn 12 points per weekly submission for the individual journal entry and 3 points per submission for the shared journal entry. '''''Late journal entries will be accepted up to one week later for up to half credit.'''''
* The instructor will read and comment on how to improve your journal entries on your user talk pages.
* Depending on the type of assignment for that week, you may be given the opportunity to make improvements to previous journal entries as the semester progresses.
* For most weeks in the semester, you will be assigned a "homework partner". You will be expected to consult with your partner in order to complete the assignment. However, unless otherwise stated, each partner must submit his or her own work as the individual journal entry (direct copies of each other's work is not allowed).
* Generally, your journal entries will consist of:
** Your electronic laboratory notebook (workflow and other documentation) for hands-on exercises and projects
** Answers to any specific questions posed in the exercise
** Acknowledgments section (see [[Week 1]] assignment for details)
** References section (see [[Week 1]] assignment for details)
** Shared reflection on your learning, assigned readings, or ethics case studies.

==== Oral Presentations ====

You will give three oral presentations in this course. The first two will be in the format of a “Journal Club” presentation where students will present and lead discussion of research articles from the primary literature. The third will be a research presentation on your final project. '''''Because that day’s class content is dependent upon each student being ready to present and lead discussion, late journal club presentations will not be accepted. An unexcused absence from a journal club presentation will result in a grade of zero for the presentation.'''''

==== Final Group Project ====



In addition to the research presentation, the culmination of your final project will be the preparation of a written laboratory report in the style of a manuscript that could be submitted to a peer-reviewed journal. Specific instructions will be posted later in the semester. '''''The Final Written Report cannot be accepted any later than Friday, May 3 at 12:00pm. The Final Written Report must be completed to receive a passing grade in the course.'''''

==== Life happens, what do I do then? Use your tokens! ====

To succeed in this course it is important to come to each class session and keep up with the work. However, I understand that circumstances may arise from time-to-time that could interfere with this. To responsibly manage these circumstances, the following token system is in place.

* Each student begins the semester with 4 tokens that can be used as follows:
** 1 token = turning in a individual journal entry up to one week later without penalty '''''or''''' dropping a missed shared journal entry from the final grade without penalty.
** 3 tokens = dropping a missed individual journal club entry from the final grade without penalty.
** 4 tokens = excusing an absence without penalty beyond the two automatically excused.
* To use tokens, the instructor must be emailed about your intention to use the token(s) at the day/time of usage (due date or absence). Requests to use tokens after one week from the due date or absence has passed will not be honored. Unused tokens have no point value.
* Up to two additional tokens may be earned by attending extra credit seminars (see below).

==== Extra Credit ====

Students may accumulate up to 12.5 points toward their final grade in extra credit by attending Biology Department seminars and completing the seminar sheets. Each seminar attended is worth 2.5 points with up to 5 seminars (12.5 points) total.

Alternately, you may elect to earn a token for attending the seminar instead of the extra credit points. Only two tokens may be earned this way, and the instructor must be notified of your intention to earn a token instead of extra credit at the time of the seminar by writing it on the seminar sheet on the day of the seminar.

Certain non-Biology Department seminars may be approved in advance for extra credit at the instructor's discretion. To receive credit for these seminars, you must turn in a one-page '''''hard copy''''' of your summary of the seminar '''''in class, within one week''''' of the date of the seminar or they will not count as extra credit.

===== Biology Department Seminar Attendance Policy =====

* To receive course credit for attending a Biology Department Seminar, students must do the following:
** Arrive early at the seminar venue (usually FEA auditorium) and obtain a paper seminar sheet from a faculty member.
*** Seminar sheets will only be available until 3:05 PM, at which time no further sheets will be distributed.
*** You must pick up the seminar sheet yourself. You may not obtain seminar sheets for others.
** Completely fill out the seminar sheet during the seminar, including:
*** Your name as it appears on PROWL
*** All course numbers, section numbers, professor and TA names for the courses for which you would like to receive credit
*** Day and time of seminar, speaker name, and title
*** Answer the other questions on the seminar sheet.
** Stay quietly in your seat for the entire seminar, including the question and answer period.
** At the end of the seminar, take a picture of the seminar sheet and upload it to the survey link accessed via a posted QR code.
** Turn in the paper seminar sheet to a faculty member before exiting the room.
*** You must turn in your own seminar sheet; you may not turn it in for someone else.
* Note that students arriving after 3:05 PM will not receive a seminar sheet and must enter through the back entrance on the second floor of the FEA auditorium so as not to disturb the seminar in progress.

=== Work Load Expectations ===

In line with [https://academics.lmu.edu/media/lmuacademics/provost/documents/LMU%20Credit%20Hour%20Policy_Final.pdf LMU’s Credit Hour Policy], the work load expectation for this course is that for every one hour (50 minutes) of classroom instruction, you will complete a minimum of two hours of out-of-class student work each week. This is a 3-unit course with 3 hours (150 minutes) of instruction per week. Thus the expectation is that you will complete 6 hours of work outside of class per week.

=== University Policy on Academic Honesty ===

Loyola Marymount University is a community dedicated to academic excellence. Academic honesty in scholarship and creative work stands at the center of LMU's academic life, and is essential for true learning and creation of knowledge to take place. As a university in the Jesuit and Marymount traditions, this community expects its members to act in accordance with the highest standards of honesty and ethics at all times. Violations of academic honesty undermine the fundamental educational mission of the University and cannot be tolerated.

Academic dishonesty will be treated as an extremely serious matter with severe consequences. '''''The minimum penalty for an instance of academic dishonesty in this course, even on a 1-point assignment or extra credit assignment, is a one-letter grade penalty in the course and a zero on the assignment.''''' It is never permissible to turn in any work that has not been authored by the student, such as work that has been copied from another student or copied from a source (including the Internet) without properly acknowledging the source. Note that students may not submit assignment or paper prompts to CourseHero, Chegg, online artificial intelligence tools, or any other such website; answers or papers derived from such sites are considered to be a direct violation of the Academic Honesty policy. It is the student's responsibility to make sure that your work meets the standard set forth in the “Academic Honesty Policy” (see http://academics.lmu.edu/honesty.) You are responsible for contacting the instructor before assignments are due to proactively resolve any questions you may have.

You are required to sign the [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]] for this course.

==== Academic Honesty Resources ====
* [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]]
* [https://academics.lmu.edu/media/lmuacademics/academichonesty/documents/Academic-Honesty-Policy-2021.pdf LMU Academic Honesty Policy and Procedures]
* [http://www.bio.davidson.edu/dept/plagiarism.html The Davidson College Department of Biology Guidelines for Using and Citing Sources]
* [[Media:BIOL367_Spring2024_GuidelinesforLiteratureCitations.pdf | Guidelines for Literature Citations in a Scientific Paper]]
** [https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_basic_rules.html APA Style for References]
* [http://dondi.lmu.build/share/misc/plagiarism.pdf Notes on plagiarism from an electrical engineering & computer science perspective]
* [http://libguides.lmu.edu/BIOL367 BIOL/CMSI 367 LibGuide]

=== Americans with Disabilities Act—Special Accommodations ===

Students with special needs who require reasonable modifications, special assistance, or accommodations in this course should promptly direct their request to the Disability Support Services (DSS) Office. Any student who currently has a documented disability (ADHD, Autism Spectrum Disorder, Learning, Physical, or Psychiatric) needing academic accommodations should contact the DSS Office (Daum Hall 2nd floor, 310-338-4216) as early in the semester as possible. All discussions will remain confidential. Please visit http://www.lmu.edu/dss for additional information. In addition, please schedule an appointment with the instructor early in the semester to discuss any accommodations for this course for which you have been approved.

=== Health and Wellness ===

There are many resources for student wellness on campus. A central website for students is: http://lionwellness.lmu.edu.

==== COVID-19 ====

All University mandated COVID-19 safety guidelines are to be followed. The [https://www.lmu.edu/together/ LMU Together] and [https://www.lmu.edu/together/resources/matrix/ Need to Know A-Z Index] websites contain updated information. If you have COVID-19 symptoms and/or test positive, please contact the COVID Support Team ([mailto:COVIDSupportTeam@lmu.edu COVIDSupportTeam@lmu.edu] or 310-568-6868) for instructions.

=== Emergency Preparedness ===

To report an emergency or suspicious activity, contact the LMU Department of Public Safety by phone (x222 or 310-338-2894) or at the nearest emergency call box. In the event of an evacuation, follow the evacuation signage throughout the building to the designated safe refuge area where you will receive further instruction from Public Safety or a Building Captain. For more safety information and preparedness tips, visit http://www.lmu.edu/emergency.

=== Revision Notice ===

If necessary, this syllabus and its contents are subject to revision; students are responsible for any changes or modifications announced in class. The most current version of this information resides on this page, the course web site at http://xmlpipedb.cs.lmu.edu/biodb/spring2024/.

Main Page

2024-04-25T21:19:46Z

Kdahlquist: /* Announcements */ comment out online seminar option

__NOTOC__
<div style="text-align: center; font-size: 175%">Loyola Marymount University</div>
<div style="text-align: center; font-size: 250%; line-height: 1.25em">'''BIOL 367-01: Biological Databases'''</div>
<div style="text-align: center; font-size: 175%; margin-bottom: 0.85em">Spring 2024</div>

<div style="float: right;">__TOC__</div>

== Announcements ==

* Don't forget to sign your class journal entries with your wiki signature! '''<nowiki>~~~~</nowiki>'''

=== Upcoming Seminars ===

''There are no more seminars for the remainder of the semester.''



== Instructor ==
* [[User:Kdahlquist|Kam D. Dahlquist]]

== Students ==

{| style="margin-left: auto; margin-right: auto"
| style="padding-right: 1em" | [[User:Hivanson| Hailey Ivanson]]
| style="padding-right: 1em" | [[User:Asandle1| Andrew Sandler]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Ckapla12| Charlotte Kaplan]]
| style="padding-right: 1em" | [[User:Nstojan1| Natalija Stojanovic]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Kmill104| Katherine Miller]]
| style="padding-right: 1em" | [[User:Msymond1| Dean Symonds]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|}

{{Final Project Links}}

== Schedule ==

The current course schedule is shown below. In addition to the listed in-class agendas, the following guidelines are also notable:

* Unless otherwise stated on the schedule, your weekly journals/assignments are due on Thursdays at 12:01am. In cases where subsequent revisions or corrections will be accepted, the instructor will provide feedback and submission deadlines on a per-assignment basis.
* Reading assignments should be completed ''before'' coming to class.

{| class="wikitable"
|-
! Week 
! Date 
! Before Class Reading 
! During Class Topic
! After Class Assignment
|- style="vertical-align:bottom;"
| rowspan="2" | 1
| 9-Jan
| 
|
* Syllabus walkthrough
* Pairwise interviews and introductions
* Academic Honesty case studies
* Wiki account setup
| rowspan="2" | [[Week 1]] (due 12:01am 1/18) [[Class Journal Week 1]] 
|- style="vertical-align:bottom;"
| 11-Jan
| [https://peerj.com/preprints/3215v1/ Dahlquist et al. (2017) ''An Invitation to Modeling'']
|
* What is a model?
* Model of a cell/model of a computer 
|- style="vertical-align:bottom;"
| rowspan="2" | 2
| 16-Jan
|
* Denning [http://dl.acm.org/ft_gateway.cfm?id=1378711 ''Voices of Computing''], [http://dl.acm.org/ft_gateway.cfm?id=1272529 ''Computing is a Natural Science''] (also available on [http://brightspace.lmu.edu/ Brightspace]).
* Janovy ''On Becoming a Biologist'' Chapter 1, available on [http://brightspace.lmu.edu/ Brightspace].
* Note that there are some ''before'' questions you should answer before completing these readings. See [[Week 1]].
|
* Discuss the Week 1 assignment
** Wiki syntax overview
** Lab session to setup User wiki page 
| rowspan="2" | [[Week 2]] (due 12:01am 1/25) [[Class Journal Week 2]] 
|- style="vertical-align:bottom;"
| 18-Jan
|
* [http://www.ncbi.nlm.nih.gov/books/NBK21134/#A5234 Brown, T.A. (2002) Ch. 1 ''Genomes 2'']
* [http://www.ncbi.nlm.nih.gov/books/NBK21121/ Brown, T.A. (2002) ''Genomes 2'', Ch. 3, especially section 3.3.2]
| DNA structure
|- style="vertical-align:bottom;"
| rowspan="2" | 3
| 23-Jan
|
* On [http://brightspace.lmu.edu Brightspace]:
** [https://www.sciencedirect.com/science/article/pii/S0968000403003025 Nirenberg (2004) ''Deciphering the Genetic Code'']
** [https://www.cell.com/trends/biochemical-sciences/fulltext/S0968-0004(04)00083-0 Kaji & Kaji (2004) ''Setting the Record Straight'']
** Moody (2004) ''Digital Code of Life'', Ch. 1
** Hayes (2004) ''Ode to the Code''
| Aipotu work session
| rowspan="2" | [[Week 3]] (due 12:01am 2/1) [[Class Journal Week 3]] 
|- style="vertical-align:bottom;"
| 25-Jan
| 
|
* Genes as models
* Central model of molecular biology
** [http://www.youtube.com/watch?v=u9dhO0iCLww Berkeley translation video]
** This [https://dnalc.cshl.edu/resources/animations/ web site] has links to animations of the replication, transcription, and translation processes.
** [http://brightspace.lmu.edu Slides on Brightspace]
* [[Media:BIOL367_Spring2024_GeneticCode-CentralModel.pdf | Paper and pencil exercise]]

|- style="vertical-align:bottom;"
| rowspan="2" | 4
| 30-Jan
|
* [http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/ Ford, Paul. “What is Code?” ''Business Week'', June 11, 2015.]
* [[Media:L01_DataManagement.pptx | DataONE: Data Management Slides]]
|
Introduction to biological databases ([[Media:2024-01-30_biological-databases-part1.pdf | part 1 slides]]) 
* What is bioinformatics?
* Open Science Ecosystem
* DataONE: Data management and the life cycle of data
* Terminology, types, four "Gold Standard" databases
| rowspan="2" | [[Week 4]] (due 12:01am 2/8) [[Class Journal Week 4]] 
|- style="vertical-align:bottom;"
| 1-Feb
|
* [[Media:L02_DataSharing.pptx | DataONE: Data Sharing Slides]]
* [https://doi.org/10.1093/nar/gkad1173 Rigden & Fernández (2024) ''NAR'' Database Issue editorial]
|
Introduction to biological databases ([[Media:2024-02-01_biological-databases-part2.pdf | part 2 slides]]) 
* A closer look at evaluating biological databases
* DataONE: Data sharing
|- style="vertical-align:bottom;"
| rowspan="2" | 5
| 6-Feb
| 
|
* Presentation Guidelines ([https://brightspace.lmu.edu .pptx is on Brightspace])
* Week 4 work session 
| rowspan="2" | [[Week 5]] (due 12:01am 2/15) [[Class Journal Week 5]] 
|- style="vertical-align:bottom;"
| 8-Feb
| 
|
Database presentations
* [[Media:Nemo_presentation.pdf | NeMO by Hailey & Dean]]
* [https://docs.google.com/presentation/d/1C74eHcvpTo0rnbQFcUnDsmG_AIPpIqLvM0t-DV95Obk/edit#slide=id.g1f0192797b8_0_30 Monarch Initiative by Katie & Andrew]
* [[Media:The_AgeAnnoMo_Database.pdf | AgeAnnoMO by Charlotte & Natalija]]

|- style="vertical-align:bottom;"
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 2: Going Deeper (Gene Expression Data and Relational Databases)'''
|-
| rowspan="2" | 6
| 13-Feb
|
* Moody (2004) ''Digital Code of Life'', Ch. 6 (on [https://brightspace.lmu.edu Brightspace])
* Original (2001) Human Genome Project articles in [https://www.nature.com/nature/volumes/409/issues/6822 ''Nature''] & [https://www.science.org/toc/science/291/5507 ''Science'']
* Special issues (2021) "The Human Genome at 20" in [https://www.nature.com/collections/febigehfbg ''Nature''] & [https://www.science.org/toc/science/371/6529 ''Science'']
| Human Genome Project
| rowspan="2" | [[Week 6]] (due 12:01am 2/22) [[Class Journal Week 6]] 
|- style="vertical-align:bottom;"
| 15-Feb
|
|
Where's my Stuff?
* Slides are on Brightspace
* An overview of computers, networks, files, web applications, web services, and databases
* Names, URLs, identifiers
** As applied to biology: genes, species
* “Stuff” on the worldwide web
** Accessing the web on a browser
|- style="vertical-align:bottom;"
| rowspan="2" | 7
| 20-Feb
| 
| [[Week 6]] work session
* Please bring ear buds/headphones if possible.

| rowspan="2" | No Week 7 Assignment
|- style="vertical-align:bottom;"
| 22-Feb
|
* [http://www.ncbi.nlm.nih.gov/books/NBK26818/#A1633 Alberts ''et al''. (2002) ''Molecular Biology of the Cell'', Ch. 8: Microarrays]
* [https://www.youtube.com/watch?v=0ATUjAxNf6U Microarray animation]
* [https://doi.org/10.1038/4462 Brown. & Botstein (1999)]
* Campbell, A.M. and Heyer, L.J. (2003), Ch 4 ([http://brightspace.lmu.edu on Brightspace])
* [https://doi.org/10.1126/science.278.5338.680 DeRisi, et al. (1997)]
| 'omics analysis
|- style="vertical-align:bottom; background-color:#e5fee8;"
| rowspan="2" | Spring Break
| 27-Feb
| rowspan="2" colspan="3" | No class
|- style="vertical-align:bottom; background-color:#e5fee8;"
| 29-Feb
|- style="vertical-align:bottom;"
| rowspan="2" | 8
| 5-Mar
|
* [https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf Ted Codd’s seminal paper “A Relational Model of Data for Large Shared Data Banks”]
* [https://dondi.lmu.build/share/db/super-basic-database-diagramming.pdf Super basic relational database concepts]
| Guest lecture: Dr. Dionisio
* Relational Databases part 1
| rowspan="2" | [[Week 8]] (due 12:01am 3/14) [[Class Journal Week 8]] 
|- style="vertical-align:bottom;"
| 7-Mar
| [https://dondi.lmu.build/share/db/super-basic-sql.pdf Super basic SQL crib sheet]
| Guest lecture: Dr. Dionisio
* Relational Databases part 2
|- style="vertical-align:bottom;"
| rowspan="2" | 9
| 12-Mar
| 
| [[Week 8]] work session 
| rowspan="2" | [[Week 9]] (due 12:01am 3/21) [[Class Journal Week 9]] 
|- style="vertical-align:bottom;"
| 14-Mar
| 
| Transcriptomic analysis (part 1)
* ANOVA
|- style="vertical-align:bottom;"
| rowspan="2" | 10
| 19-Mar
| [https://xkcd.com/882/ "Significant"]
| Transcriptomic analysis (part 2)
* Multiple testing problem, p value corrections
| rowspan="2" | [[Week 10]] (due 12:01am 4/4, interim deadlines on 3/26 and 4/2) [[Class Journal Week 10]] 
|- style="vertical-align:bottom;"
| 21-Mar
|
* [https://academic.oup.com/bioinformatics/article/21/suppl_1/i159/203147 Ernst, J., & Bar-Joseph, Z. (2006). STEM]
* [https://doi.org/10.1038/75556 Ashburner et al. (2000). Gene Ontology]
| Transcriptomic analysis (part 3)
* Clustering and GO term enrichment analysis
|- style="vertical-align:bottom;"
| 11
| 26-Mar
|
* [https://doi.org/10.1093/nar/gkac1041 Teixeira, et al. (2023) YEASTRACT+]
* [https://link.springer.com/article/10.1007/s11538-015-0092-6 Dahlquist et al. (2015) GRNmap]
* [https://peerj.com/articles/cs-85/ Dahlquist et al. (2016) GRNsight]
|
* Transcriptomic analysis (part 4)
** GRN modeling and visualization
| rowspan="2" | Continue with [[Week 10]] assignment
|- style="vertical-align:bottom; background-color:#e5fee8;"
| Easter
| 28-Mar
| colspan="2" | No class
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 3: Integrating for Research (GRNsight Gene Expression Database Project)'''
|-
|- style="vertical-align:bottom;"
| rowspan="2" | 12
| 2-Apr
| 
| Discussion of [[Week 10]] results
| rowspan="2" | [[Week 12]] (due 12:01am 4/11) 
|- style="vertical-align:bottom;"
| 4-Apr
| 
| Begin Database Project
* Overview of project
* Work session for journal club
|- style="vertical-align:bottom;"
| rowspan="2" | 13
| 9-Apr
| 
| Work session for journal club
| rowspan="2" | [[Week 13]] (due 12:01am 4/18) 
|- style="vertical-align:bottom;"
| 11-Apr
| 
|
* Journal Club Presentations
* Work session to organize milestones
|- style="vertical-align:bottom;"
| rowspan="2" | 14
| 16-Jan
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 14]] (due 12:01am 4/25) 
|- style="vertical-align:bottom;"
| 18-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom;"
| rowspan="2" | 15
| 23-Apr
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 15]] (due 12:00 noon 5/3) 
|- style="vertical-align:bottom;"
| 25-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom; background-color:#ffccc9;"
| rowspan="2" | Finals
| 2-May
|
| '''Final Presentations 11:00am''' 
| rowspan="2" |
|- style="vertical-align:bottom; background-color:#ffccc9;"
| 3-May
|
| '''Project Deliverables Due 12:00 noon''' 
|}

== Course Information ==

=== Instructor ===

==== [[User:Kdahlquist | Kam D. Dahlquist, Ph.D.]] ====
: http://kdahlquist.github.io/DahlquistLab/index.htm
: '''Phone:''' (310) 338-7697
: '''E-mail:''' kdahlquist at lmu dot edu
: '''Office:''' Life Sciences Building 289
: '''Office Hours (Spring 2024):''' Mondays 2:00-3:30 PM, Tuesdays 3:15-4:45, and by appointment; check [https://brightspace.lmu.edu Brightspace] for a Calendly link to make an appointment for a Zoom or in-person meeting.

=== Prerequisites/Recommended Background ===

BIOL 201 and MATH 123 or MATH 132 or MATH 204 or MATH 205.

=== Class Meetings and Attendance ===
TR 1:45-3:00pm, Seaver 120 

This is a hands-on, participatory course, thus attendance at all class meetings is required. Each student is allowed two “sick” days (automatically excused absences) during the semester. Further unexcused absences from class will result in a 12 point (2.5%) deduction from the overall course grade for each absence. Every effort should be made to attend class on oral presentation days as the content of that day's class is dependent on student participation. Unexcused absences from an oral presentation will result in a grade of zero for the presentation. The instructor should be notified as soon as possible, electronically or by phone, of the reasons for all absences.

Note that the last day to add or drop a class without a grade of W is January 12. The withdrawal or credit/no-credit status deadline is April 5.

=== Mutual Responsibilities ===

This course is designed to foster your development as a biologist and computer scientist and to give you an authentic research experience. We will be engaged together in discovering, examining, and practicing the personal qualities, technical skills, and community standards of the scientific community. While you are ultimately responsible for your own learning, you are not alone. Our class constitutes a team where we will be learning from each other. The role of the instructor is to provide the expert coaching to support and assist you on your journey. All of the exercises, readings, assignments, and policies detailed below have been designed with this purpose in mind.

=== Classroom Conduct ===

We are all responsible for maintaining a classroom and laboratory environment that is safe and conducive to learning. As such, we will observe the following:

# As an LMU Lion, by the [http://studentaffairs.lmu.edu/wellness/lmucares/aboutlmucares/livethelionscode/ Lion’s code], you are pledged to join the discourse of the academy with honesty of voice and integrity of scholarship and to show respect for staff, professors, and other students.
# You are responsible for your own learning and for being a good class citizen.
# Class will start promptly on time.
# You are expected to come to class having done the assigned reading and preparatory work so that you are ready to participate in discussions and to perform the laboratory exercises.
# You are expected to bring the required materials to each class session.
# Cell phones and other ancillary devices must be turned off and put away out of sight. Your own laptop and/or tablet may be used to conduct the class exercises, '''''provided that you have confirmed with the instructor that you have the correct versions of software installed for the exercise'''''. If, however, the laptops/tablets are being used for other purposes and become distracting to you or others, you will be asked to put them away.
# All students are governed by the [https://lmu.box.com/s/urox7s2vkxtoofg0rmmnv5h7ik5rahof Student Conduct Code]. Disruptive behavior which is persistent or significantly interferes with classroom activities may be subject to disciplinary action. A student may be referred to the Office of Student Judicial Affairs if his or her behavior constitutes a violation of the conduct code.

=== Course Website ===

This is the course web site and wiki, hosted by http://xmlpipedb.cs.lmu.edu/biodb/spring2024/. You will need to have a user account on this wiki to be able to edit the wiki and complete coursework. Updates to the course schedule and electronic copies of all handouts, assignments, and readings will be posted to this site. You will also use the site to keep an electronic lab notebook/journal for the course. In addition, students have been automatically enrolled in the course page on [http://brightspace.lmu.edu Brightspace]. The site will be used for materials that cannot be made public on this wiki, including grades.

=== Email Communication ===

At times I will communicate with the entire class using campus email systems, so it is essential that you regularly check your lion.lmu.edu email address or forward your lion account email to your preferred email address. Messages sent to the instructor at night or on the weekend will be answered the next school day.

=== Required Materials ===

==== Texts ====

There is no required text to purchase for the course; materials will be put on reserve at Hannon Library or will be available online on this wiki or [http://brightspace.lmu.edu Brightspace] site. Specific reading assignments are given on the course schedule and should be completed before coming to class.
* Assorted handouts, articles, and sample code will be distributed throughout the semester.
* Additional information is also available on the web; do not hesitate to look for further sources of information regarding the concepts, techniques, tools, and paradigms that we will discuss.

==== Materials (must be brought to each class meeting) ====

* 3-ring binder or folder with all course handouts
* Pen, pencil, extra paper
* USB flash drive to back-up data
* Account for this wiki
* [http://www.github.com GitHub account]

=== Course Description ===

The disciplines of biology and computer science come together in bioinformatics, where computational tools are needed to manage and analyze the flood of data coming from new genomics technologies. Biological databases form a significant part of this young and exciting field. This course introduces students to both the biology and computer science expertise needed to understand, use, and develop biological databases. Biology topics include the fundamentals of genetics, molecular biology, and biochemistry needed to understand the data stored in biological databases, as well as the biotechnologies used to gather these data in a high-throughput manner. Computer science topics include what biological databases are, why they are important (and needed), and the challenges that arise in compiling them effectively. Biology and computer science lectures on topics that are relevant to biological databases are coupled with hands-on experience with a variety of software packages ranging from bioinformatics utilities to general-purpose database and software development tools. After learning how to use a biological database, students will be asked to build one of their own.

==== Course Objectives and Learning Outcomes ====

This course is built upon L. Dee Fink’s ''taxonomy of significant learning'', as applied to biological databases. Long after the course concludes, our hope is that:
* You understand how biological information is encoded in the genome and can apply this knowledge to a variety of biological tasks and problems
* You understand the core concepts, structure, and functions of a database, ranging from individual files to a full relational database management system, and can perform useful tasks with such data
* You show discipline and proficiency in day-to-day science and engineering best practices, such as maintaining journals and notebooks, managing your files and code, and critically evaluating scientific and technical information
* You recognize and care about how the biological and technological issues presented in this course relate to and affect society, our daily lives, and ourselves
* You have some skills and tools for “leaving your comfort zone,” flourishing outside of it, and learning more about biology and computer science on your own
* You learn how to communicate and work effectively with colleagues from your discipline and different disciplines

==== University Core Curriculum ====

This course fulfills the following requirements in the University Core Curriculum:
* Integrations: Interdisciplinary Connections

=== Course Work and Grading ===

Your work in this course will be assessed in the following areas:

{| style="border: 1px dashed rgb(47, 111, 171); background: rgb(249, 249, 249); margin: 1em 0; padding: 1em" cellpadding="5ex"
| Weekly electronic lab notebook/journal assignments, individual (usually 12 points each)
| style="text-align: right" | 168 
| points
|-
| Weekly electronic lab notebook/journal assignments, shared (usually 3 points each)
| style="text-align: right" | 42 
| points
|-
| Oral presentations (3 @ 35, 45, 60 points)
| style="text-align: right" | 140
| points 
|-
| Final Project Deliverables (including written report)
| style="text-align: right" | 100
| points
|-
| '''Total'''
| style="text-align: right" | '''450''' 
| '''points'''
|}

Final course grading scale:
94.0-100.0% A
90.0- 93.9% A-
86.0- 89.9% B+
82.0- 85.9% B
78.0- 81.9% B-
74.0- 77.9% C+
70.0- 73.9% C
67.0- 69.9% C-
60.0- 66.9% D
≤ 59.9% F

Current grades will be made available at [http://brightspace.lmu.edu Brightspace].

==== Electronic Laboratory Notebook/Journal ====

One of the most important skills you can develop as a scientist is keeping an excellent laboratory notebook. For computational research, the equivalent of the biology paper-based lab notebook is documentation of your “workflow.” For this course you will practice documentation skills by keeping an electronic lab notebook or journal. The technology we will use is this wiki that we will create and edit during the semester. The wiki software is the same one that runs Wikipedia and many other wiki sites, so proficiency gained here is easily transferable to other applications.

You will create an individual user page and make weekly entries that the instructor will read and grade. You will use the wiki to complete the assignments as well. The following guidelines apply:
* Your weekly journal entry is typically due every 12:01am on Thursday Pacific time; consult the schedule for specific due dates for each assignment.
* Each weekly assignment has an individual component and a shared component. You will earn 12 points per weekly submission for the individual journal entry and 3 points per submission for the shared journal entry. '''''Late journal entries will be accepted up to one week later for up to half credit.'''''
* The instructor will read and comment on how to improve your journal entries on your user talk pages.
* Depending on the type of assignment for that week, you may be given the opportunity to make improvements to previous journal entries as the semester progresses.
* For most weeks in the semester, you will be assigned a "homework partner". You will be expected to consult with your partner in order to complete the assignment. However, unless otherwise stated, each partner must submit his or her own work as the individual journal entry (direct copies of each other's work is not allowed).
* Generally, your journal entries will consist of:
** Your electronic laboratory notebook (workflow and other documentation) for hands-on exercises and projects
** Answers to any specific questions posed in the exercise
** Acknowledgments section (see [[Week 1]] assignment for details)
** References section (see [[Week 1]] assignment for details)
** Shared reflection on your learning, assigned readings, or ethics case studies.

==== Oral Presentations ====

You will give three oral presentations in this course. The first two will be in the format of a “Journal Club” presentation where students will present and lead discussion of research articles from the primary literature. The third will be a research presentation on your final project. '''''Because that day’s class content is dependent upon each student being ready to present and lead discussion, late journal club presentations will not be accepted. An unexcused absence from a journal club presentation will result in a grade of zero for the presentation.'''''

==== Final Group Project ====



In addition to the research presentation, the culmination of your final project will be the preparation of a written laboratory report in the style of a manuscript that could be submitted to a peer-reviewed journal. Specific instructions will be posted later in the semester. '''''The Final Written Report cannot be accepted any later than Friday, May 3 at 12:00pm. The Final Written Report must be completed to receive a passing grade in the course.'''''

==== Life happens, what do I do then? Use your tokens! ====

To succeed in this course it is important to come to each class session and keep up with the work. However, I understand that circumstances may arise from time-to-time that could interfere with this. To responsibly manage these circumstances, the following token system is in place.

* Each student begins the semester with 4 tokens that can be used as follows:
** 1 token = turning in a individual journal entry up to one week later without penalty '''''or''''' dropping a missed shared journal entry from the final grade without penalty.
** 3 tokens = dropping a missed individual journal club entry from the final grade without penalty.
** 4 tokens = excusing an absence without penalty beyond the two automatically excused.
* To use tokens, the instructor must be emailed about your intention to use the token(s) at the day/time of usage (due date or absence). Requests to use tokens after one week from the due date or absence has passed will not be honored. Unused tokens have no point value.
* Up to two additional tokens may be earned by attending extra credit seminars (see below).

==== Extra Credit ====

Students may accumulate up to 12.5 points toward their final grade in extra credit by attending Biology Department seminars and completing the seminar sheets. Each seminar attended is worth 2.5 points with up to 5 seminars (12.5 points) total.

Alternately, you may elect to earn a token for attending the seminar instead of the extra credit points. Only two tokens may be earned this way, and the instructor must be notified of your intention to earn a token instead of extra credit at the time of the seminar by writing it on the seminar sheet on the day of the seminar.

Certain non-Biology Department seminars may be approved in advance for extra credit at the instructor's discretion. To receive credit for these seminars, you must turn in a one-page '''''hard copy''''' of your summary of the seminar '''''in class, within one week''''' of the date of the seminar or they will not count as extra credit.

===== Biology Department Seminar Attendance Policy =====

* To receive course credit for attending a Biology Department Seminar, students must do the following:
** Arrive early at the seminar venue (usually FEA auditorium) and obtain a paper seminar sheet from a faculty member.
*** Seminar sheets will only be available until 3:05 PM, at which time no further sheets will be distributed.
*** You must pick up the seminar sheet yourself. You may not obtain seminar sheets for others.
** Completely fill out the seminar sheet during the seminar, including:
*** Your name as it appears on PROWL
*** All course numbers, section numbers, professor and TA names for the courses for which you would like to receive credit
*** Day and time of seminar, speaker name, and title
*** Answer the other questions on the seminar sheet.
** Stay quietly in your seat for the entire seminar, including the question and answer period.
** At the end of the seminar, take a picture of the seminar sheet and upload it to the survey link accessed via a posted QR code.
** Turn in the paper seminar sheet to a faculty member before exiting the room.
*** You must turn in your own seminar sheet; you may not turn it in for someone else.
* Note that students arriving after 3:05 PM will not receive a seminar sheet and must enter through the back entrance on the second floor of the FEA auditorium so as not to disturb the seminar in progress.

=== Work Load Expectations ===

In line with [https://academics.lmu.edu/media/lmuacademics/provost/documents/LMU%20Credit%20Hour%20Policy_Final.pdf LMU’s Credit Hour Policy], the work load expectation for this course is that for every one hour (50 minutes) of classroom instruction, you will complete a minimum of two hours of out-of-class student work each week. This is a 3-unit course with 3 hours (150 minutes) of instruction per week. Thus the expectation is that you will complete 6 hours of work outside of class per week.

=== University Policy on Academic Honesty ===

Loyola Marymount University is a community dedicated to academic excellence. Academic honesty in scholarship and creative work stands at the center of LMU's academic life, and is essential for true learning and creation of knowledge to take place. As a university in the Jesuit and Marymount traditions, this community expects its members to act in accordance with the highest standards of honesty and ethics at all times. Violations of academic honesty undermine the fundamental educational mission of the University and cannot be tolerated.

Academic dishonesty will be treated as an extremely serious matter with severe consequences. '''''The minimum penalty for an instance of academic dishonesty in this course, even on a 1-point assignment or extra credit assignment, is a one-letter grade penalty in the course and a zero on the assignment.''''' It is never permissible to turn in any work that has not been authored by the student, such as work that has been copied from another student or copied from a source (including the Internet) without properly acknowledging the source. Note that students may not submit assignment or paper prompts to CourseHero, Chegg, online artificial intelligence tools, or any other such website; answers or papers derived from such sites are considered to be a direct violation of the Academic Honesty policy. It is the student's responsibility to make sure that your work meets the standard set forth in the “Academic Honesty Policy” (see http://academics.lmu.edu/honesty.) You are responsible for contacting the instructor before assignments are due to proactively resolve any questions you may have.

You are required to sign the [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]] for this course.

==== Academic Honesty Resources ====
* [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]]
* [https://academics.lmu.edu/media/lmuacademics/academichonesty/documents/Academic-Honesty-Policy-2021.pdf LMU Academic Honesty Policy and Procedures]
* [http://www.bio.davidson.edu/dept/plagiarism.html The Davidson College Department of Biology Guidelines for Using and Citing Sources]
* [[Media:BIOL367_Spring2024_GuidelinesforLiteratureCitations.pdf | Guidelines for Literature Citations in a Scientific Paper]]
** [https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_basic_rules.html APA Style for References]
* [http://dondi.lmu.build/share/misc/plagiarism.pdf Notes on plagiarism from an electrical engineering & computer science perspective]
* [http://libguides.lmu.edu/BIOL367 BIOL/CMSI 367 LibGuide]

=== Americans with Disabilities Act—Special Accommodations ===

Students with special needs who require reasonable modifications, special assistance, or accommodations in this course should promptly direct their request to the Disability Support Services (DSS) Office. Any student who currently has a documented disability (ADHD, Autism Spectrum Disorder, Learning, Physical, or Psychiatric) needing academic accommodations should contact the DSS Office (Daum Hall 2nd floor, 310-338-4216) as early in the semester as possible. All discussions will remain confidential. Please visit http://www.lmu.edu/dss for additional information. In addition, please schedule an appointment with the instructor early in the semester to discuss any accommodations for this course for which you have been approved.

=== Health and Wellness ===

There are many resources for student wellness on campus. A central website for students is: http://lionwellness.lmu.edu.

==== COVID-19 ====

All University mandated COVID-19 safety guidelines are to be followed. The [https://www.lmu.edu/together/ LMU Together] and [https://www.lmu.edu/together/resources/matrix/ Need to Know A-Z Index] websites contain updated information. If you have COVID-19 symptoms and/or test positive, please contact the COVID Support Team ([mailto:COVIDSupportTeam@lmu.edu COVIDSupportTeam@lmu.edu] or 310-568-6868) for instructions.

=== Emergency Preparedness ===

To report an emergency or suspicious activity, contact the LMU Department of Public Safety by phone (x222 or 310-338-2894) or at the nearest emergency call box. In the event of an evacuation, follow the evacuation signage throughout the building to the designated safe refuge area where you will receive further instruction from Public Safety or a Building Captain. For more safety information and preparedness tips, visit http://www.lmu.edu/emergency.

=== Revision Notice ===

If necessary, this syllabus and its contents are subject to revision; students are responsible for any changes or modifications announced in class. The most current version of this information resides on this page, the course web site at http://xmlpipedb.cs.lmu.edu/biodb/spring2024/.

Main Page

2024-04-23T21:06:31Z

Kdahlquist: /* Upcoming Seminars */ no more seminars

__NOTOC__
<div style="text-align: center; font-size: 175%">Loyola Marymount University</div>
<div style="text-align: center; font-size: 250%; line-height: 1.25em">'''BIOL 367-01: Biological Databases'''</div>
<div style="text-align: center; font-size: 175%; margin-bottom: 0.85em">Spring 2024</div>

<div style="float: right;">__TOC__</div>

== Announcements ==

* Don't forget to sign your class journal entries with your wiki signature! '''<nowiki>~~~~</nowiki>'''

=== Upcoming Seminars ===

''There are no more seminars for the remainder of the semester.''

=== Online Extra Credit Seminar Option ===

* You may earn 1 extra credit seminar by watching a video seminar and doing a 1-page write-up of what you learned from the seminar.
** Select a seminar from the [https://www.ibiology.org/research-talks/genetics-and-gene-regulation/ iBiology series on Genetics and Gene Regulation].
** It needs to be a seminar (with one scientist talking + slides) not an educational video.
** The total length of the seminar needs to be >= 50 minutes. You might need to watch two parts to achieve that length.
** Write a one-page reflection on what you learned from the seminar.
** Reflections are due in hard copy on the last day of class, Thursday, April 25.

== Instructor ==
* [[User:Kdahlquist|Kam D. Dahlquist]]

== Students ==

{| style="margin-left: auto; margin-right: auto"
| style="padding-right: 1em" | [[User:Hivanson| Hailey Ivanson]]
| style="padding-right: 1em" | [[User:Asandle1| Andrew Sandler]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Ckapla12| Charlotte Kaplan]]
| style="padding-right: 1em" | [[User:Nstojan1| Natalija Stojanovic]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" | [[User:Kmill104| Katherine Miller]]
| style="padding-right: 1em" | [[User:Msymond1| Dean Symonds]]
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|-
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
| style="padding-right: 1em" |
|}

{{Final Project Links}}

== Schedule ==

The current course schedule is shown below. In addition to the listed in-class agendas, the following guidelines are also notable:

* Unless otherwise stated on the schedule, your weekly journals/assignments are due on Thursdays at 12:01am. In cases where subsequent revisions or corrections will be accepted, the instructor will provide feedback and submission deadlines on a per-assignment basis.
* Reading assignments should be completed ''before'' coming to class.

{| class="wikitable"
|-
! Week 
! Date 
! Before Class Reading 
! During Class Topic
! After Class Assignment
|- style="vertical-align:bottom;"
| rowspan="2" | 1
| 9-Jan
| 
|
* Syllabus walkthrough
* Pairwise interviews and introductions
* Academic Honesty case studies
* Wiki account setup
| rowspan="2" | [[Week 1]] (due 12:01am 1/18) [[Class Journal Week 1]] 
|- style="vertical-align:bottom;"
| 11-Jan
| [https://peerj.com/preprints/3215v1/ Dahlquist et al. (2017) ''An Invitation to Modeling'']
|
* What is a model?
* Model of a cell/model of a computer 
|- style="vertical-align:bottom;"
| rowspan="2" | 2
| 16-Jan
|
* Denning [http://dl.acm.org/ft_gateway.cfm?id=1378711 ''Voices of Computing''], [http://dl.acm.org/ft_gateway.cfm?id=1272529 ''Computing is a Natural Science''] (also available on [http://brightspace.lmu.edu/ Brightspace]).
* Janovy ''On Becoming a Biologist'' Chapter 1, available on [http://brightspace.lmu.edu/ Brightspace].
* Note that there are some ''before'' questions you should answer before completing these readings. See [[Week 1]].
|
* Discuss the Week 1 assignment
** Wiki syntax overview
** Lab session to setup User wiki page 
| rowspan="2" | [[Week 2]] (due 12:01am 1/25) [[Class Journal Week 2]] 
|- style="vertical-align:bottom;"
| 18-Jan
|
* [http://www.ncbi.nlm.nih.gov/books/NBK21134/#A5234 Brown, T.A. (2002) Ch. 1 ''Genomes 2'']
* [http://www.ncbi.nlm.nih.gov/books/NBK21121/ Brown, T.A. (2002) ''Genomes 2'', Ch. 3, especially section 3.3.2]
| DNA structure
|- style="vertical-align:bottom;"
| rowspan="2" | 3
| 23-Jan
|
* On [http://brightspace.lmu.edu Brightspace]:
** [https://www.sciencedirect.com/science/article/pii/S0968000403003025 Nirenberg (2004) ''Deciphering the Genetic Code'']
** [https://www.cell.com/trends/biochemical-sciences/fulltext/S0968-0004(04)00083-0 Kaji & Kaji (2004) ''Setting the Record Straight'']
** Moody (2004) ''Digital Code of Life'', Ch. 1
** Hayes (2004) ''Ode to the Code''
| Aipotu work session
| rowspan="2" | [[Week 3]] (due 12:01am 2/1) [[Class Journal Week 3]] 
|- style="vertical-align:bottom;"
| 25-Jan
| 
|
* Genes as models
* Central model of molecular biology
** [http://www.youtube.com/watch?v=u9dhO0iCLww Berkeley translation video]
** This [https://dnalc.cshl.edu/resources/animations/ web site] has links to animations of the replication, transcription, and translation processes.
** [http://brightspace.lmu.edu Slides on Brightspace]
* [[Media:BIOL367_Spring2024_GeneticCode-CentralModel.pdf | Paper and pencil exercise]]

|- style="vertical-align:bottom;"
| rowspan="2" | 4
| 30-Jan
|
* [http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/ Ford, Paul. “What is Code?” ''Business Week'', June 11, 2015.]
* [[Media:L01_DataManagement.pptx | DataONE: Data Management Slides]]
|
Introduction to biological databases ([[Media:2024-01-30_biological-databases-part1.pdf | part 1 slides]]) 
* What is bioinformatics?
* Open Science Ecosystem
* DataONE: Data management and the life cycle of data
* Terminology, types, four "Gold Standard" databases
| rowspan="2" | [[Week 4]] (due 12:01am 2/8) [[Class Journal Week 4]] 
|- style="vertical-align:bottom;"
| 1-Feb
|
* [[Media:L02_DataSharing.pptx | DataONE: Data Sharing Slides]]
* [https://doi.org/10.1093/nar/gkad1173 Rigden & Fernández (2024) ''NAR'' Database Issue editorial]
|
Introduction to biological databases ([[Media:2024-02-01_biological-databases-part2.pdf | part 2 slides]]) 
* A closer look at evaluating biological databases
* DataONE: Data sharing
|- style="vertical-align:bottom;"
| rowspan="2" | 5
| 6-Feb
| 
|
* Presentation Guidelines ([https://brightspace.lmu.edu .pptx is on Brightspace])
* Week 4 work session 
| rowspan="2" | [[Week 5]] (due 12:01am 2/15) [[Class Journal Week 5]] 
|- style="vertical-align:bottom;"
| 8-Feb
| 
|
Database presentations
* [[Media:Nemo_presentation.pdf | NeMO by Hailey & Dean]]
* [https://docs.google.com/presentation/d/1C74eHcvpTo0rnbQFcUnDsmG_AIPpIqLvM0t-DV95Obk/edit#slide=id.g1f0192797b8_0_30 Monarch Initiative by Katie & Andrew]
* [[Media:The_AgeAnnoMo_Database.pdf | AgeAnnoMO by Charlotte & Natalija]]

|- style="vertical-align:bottom;"
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 2: Going Deeper (Gene Expression Data and Relational Databases)'''
|-
| rowspan="2" | 6
| 13-Feb
|
* Moody (2004) ''Digital Code of Life'', Ch. 6 (on [https://brightspace.lmu.edu Brightspace])
* Original (2001) Human Genome Project articles in [https://www.nature.com/nature/volumes/409/issues/6822 ''Nature''] & [https://www.science.org/toc/science/291/5507 ''Science'']
* Special issues (2021) "The Human Genome at 20" in [https://www.nature.com/collections/febigehfbg ''Nature''] & [https://www.science.org/toc/science/371/6529 ''Science'']
| Human Genome Project
| rowspan="2" | [[Week 6]] (due 12:01am 2/22) [[Class Journal Week 6]] 
|- style="vertical-align:bottom;"
| 15-Feb
|
|
Where's my Stuff?
* Slides are on Brightspace
* An overview of computers, networks, files, web applications, web services, and databases
* Names, URLs, identifiers
** As applied to biology: genes, species
* “Stuff” on the worldwide web
** Accessing the web on a browser
|- style="vertical-align:bottom;"
| rowspan="2" | 7
| 20-Feb
| 
| [[Week 6]] work session
* Please bring ear buds/headphones if possible.

| rowspan="2" | No Week 7 Assignment
|- style="vertical-align:bottom;"
| 22-Feb
|
* [http://www.ncbi.nlm.nih.gov/books/NBK26818/#A1633 Alberts ''et al''. (2002) ''Molecular Biology of the Cell'', Ch. 8: Microarrays]
* [https://www.youtube.com/watch?v=0ATUjAxNf6U Microarray animation]
* [https://doi.org/10.1038/4462 Brown. & Botstein (1999)]
* Campbell, A.M. and Heyer, L.J. (2003), Ch 4 ([http://brightspace.lmu.edu on Brightspace])
* [https://doi.org/10.1126/science.278.5338.680 DeRisi, et al. (1997)]
| 'omics analysis
|- style="vertical-align:bottom; background-color:#e5fee8;"
| rowspan="2" | Spring Break
| 27-Feb
| rowspan="2" colspan="3" | No class
|- style="vertical-align:bottom; background-color:#e5fee8;"
| 29-Feb
|- style="vertical-align:bottom;"
| rowspan="2" | 8
| 5-Mar
|
* [https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf Ted Codd’s seminal paper “A Relational Model of Data for Large Shared Data Banks”]
* [https://dondi.lmu.build/share/db/super-basic-database-diagramming.pdf Super basic relational database concepts]
| Guest lecture: Dr. Dionisio
* Relational Databases part 1
| rowspan="2" | [[Week 8]] (due 12:01am 3/14) [[Class Journal Week 8]] 
|- style="vertical-align:bottom;"
| 7-Mar
| [https://dondi.lmu.build/share/db/super-basic-sql.pdf Super basic SQL crib sheet]
| Guest lecture: Dr. Dionisio
* Relational Databases part 2
|- style="vertical-align:bottom;"
| rowspan="2" | 9
| 12-Mar
| 
| [[Week 8]] work session 
| rowspan="2" | [[Week 9]] (due 12:01am 3/21) [[Class Journal Week 9]] 
|- style="vertical-align:bottom;"
| 14-Mar
| 
| Transcriptomic analysis (part 1)
* ANOVA
|- style="vertical-align:bottom;"
| rowspan="2" | 10
| 19-Mar
| [https://xkcd.com/882/ "Significant"]
| Transcriptomic analysis (part 2)
* Multiple testing problem, p value corrections
| rowspan="2" | [[Week 10]] (due 12:01am 4/4, interim deadlines on 3/26 and 4/2) [[Class Journal Week 10]] 
|- style="vertical-align:bottom;"
| 21-Mar
|
* [https://academic.oup.com/bioinformatics/article/21/suppl_1/i159/203147 Ernst, J., & Bar-Joseph, Z. (2006). STEM]
* [https://doi.org/10.1038/75556 Ashburner et al. (2000). Gene Ontology]
| Transcriptomic analysis (part 3)
* Clustering and GO term enrichment analysis
|- style="vertical-align:bottom;"
| 11
| 26-Mar
|
* [https://doi.org/10.1093/nar/gkac1041 Teixeira, et al. (2023) YEASTRACT+]
* [https://link.springer.com/article/10.1007/s11538-015-0092-6 Dahlquist et al. (2015) GRNmap]
* [https://peerj.com/articles/cs-85/ Dahlquist et al. (2016) GRNsight]
|
* Transcriptomic analysis (part 4)
** GRN modeling and visualization
| rowspan="2" | Continue with [[Week 10]] assignment
|- style="vertical-align:bottom; background-color:#e5fee8;"
| Easter
| 28-Mar
| colspan="2" | No class
|- style="background-color:#dae8fc;"
| colspan="5" | '''Part 3: Integrating for Research (GRNsight Gene Expression Database Project)'''
|-
|- style="vertical-align:bottom;"
| rowspan="2" | 12
| 2-Apr
| 
| Discussion of [[Week 10]] results
| rowspan="2" | [[Week 12]] (due 12:01am 4/11) 
|- style="vertical-align:bottom;"
| 4-Apr
| 
| Begin Database Project
* Overview of project
* Work session for journal club
|- style="vertical-align:bottom;"
| rowspan="2" | 13
| 9-Apr
| 
| Work session for journal club
| rowspan="2" | [[Week 13]] (due 12:01am 4/18) 
|- style="vertical-align:bottom;"
| 11-Apr
| 
|
* Journal Club Presentations
* Work session to organize milestones
|- style="vertical-align:bottom;"
| rowspan="2" | 14
| 16-Jan
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 14]] (due 12:01am 4/25) 
|- style="vertical-align:bottom;"
| 18-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom;"
| rowspan="2" | 15
| 23-Apr
| 
|
* Status report
* Work session
| rowspan="2" | [[Week 15]] (due 12:00 noon 5/3) 
|- style="vertical-align:bottom;"
| 25-Apr
| 
|
* Status report
* Work session
|- style="vertical-align:bottom; background-color:#ffccc9;"
| rowspan="2" | Finals
| 2-May
|
| '''Final Presentations 11:00am''' 
| rowspan="2" |
|- style="vertical-align:bottom; background-color:#ffccc9;"
| 3-May
|
| '''Project Deliverables Due 12:00 noon''' 
|}

== Course Information ==

=== Instructor ===

==== [[User:Kdahlquist | Kam D. Dahlquist, Ph.D.]] ====
: http://kdahlquist.github.io/DahlquistLab/index.htm
: '''Phone:''' (310) 338-7697
: '''E-mail:''' kdahlquist at lmu dot edu
: '''Office:''' Life Sciences Building 289
: '''Office Hours (Spring 2024):''' Mondays 2:00-3:30 PM, Tuesdays 3:15-4:45, and by appointment; check [https://brightspace.lmu.edu Brightspace] for a Calendly link to make an appointment for a Zoom or in-person meeting.

=== Prerequisites/Recommended Background ===

BIOL 201 and MATH 123 or MATH 132 or MATH 204 or MATH 205.

=== Class Meetings and Attendance ===
TR 1:45-3:00pm, Seaver 120 

This is a hands-on, participatory course, thus attendance at all class meetings is required. Each student is allowed two “sick” days (automatically excused absences) during the semester. Further unexcused absences from class will result in a 12 point (2.5%) deduction from the overall course grade for each absence. Every effort should be made to attend class on oral presentation days as the content of that day's class is dependent on student participation. Unexcused absences from an oral presentation will result in a grade of zero for the presentation. The instructor should be notified as soon as possible, electronically or by phone, of the reasons for all absences.

Note that the last day to add or drop a class without a grade of W is January 12. The withdrawal or credit/no-credit status deadline is April 5.

=== Mutual Responsibilities ===

This course is designed to foster your development as a biologist and computer scientist and to give you an authentic research experience. We will be engaged together in discovering, examining, and practicing the personal qualities, technical skills, and community standards of the scientific community. While you are ultimately responsible for your own learning, you are not alone. Our class constitutes a team where we will be learning from each other. The role of the instructor is to provide the expert coaching to support and assist you on your journey. All of the exercises, readings, assignments, and policies detailed below have been designed with this purpose in mind.

=== Classroom Conduct ===

We are all responsible for maintaining a classroom and laboratory environment that is safe and conducive to learning. As such, we will observe the following:

# As an LMU Lion, by the [http://studentaffairs.lmu.edu/wellness/lmucares/aboutlmucares/livethelionscode/ Lion’s code], you are pledged to join the discourse of the academy with honesty of voice and integrity of scholarship and to show respect for staff, professors, and other students.
# You are responsible for your own learning and for being a good class citizen.
# Class will start promptly on time.
# You are expected to come to class having done the assigned reading and preparatory work so that you are ready to participate in discussions and to perform the laboratory exercises.
# You are expected to bring the required materials to each class session.
# Cell phones and other ancillary devices must be turned off and put away out of sight. Your own laptop and/or tablet may be used to conduct the class exercises, '''''provided that you have confirmed with the instructor that you have the correct versions of software installed for the exercise'''''. If, however, the laptops/tablets are being used for other purposes and become distracting to you or others, you will be asked to put them away.
# All students are governed by the [https://lmu.box.com/s/urox7s2vkxtoofg0rmmnv5h7ik5rahof Student Conduct Code]. Disruptive behavior which is persistent or significantly interferes with classroom activities may be subject to disciplinary action. A student may be referred to the Office of Student Judicial Affairs if his or her behavior constitutes a violation of the conduct code.

=== Course Website ===

This is the course web site and wiki, hosted by http://xmlpipedb.cs.lmu.edu/biodb/spring2024/. You will need to have a user account on this wiki to be able to edit the wiki and complete coursework. Updates to the course schedule and electronic copies of all handouts, assignments, and readings will be posted to this site. You will also use the site to keep an electronic lab notebook/journal for the course. In addition, students have been automatically enrolled in the course page on [http://brightspace.lmu.edu Brightspace]. The site will be used for materials that cannot be made public on this wiki, including grades.

=== Email Communication ===

At times I will communicate with the entire class using campus email systems, so it is essential that you regularly check your lion.lmu.edu email address or forward your lion account email to your preferred email address. Messages sent to the instructor at night or on the weekend will be answered the next school day.

=== Required Materials ===

==== Texts ====

There is no required text to purchase for the course; materials will be put on reserve at Hannon Library or will be available online on this wiki or [http://brightspace.lmu.edu Brightspace] site. Specific reading assignments are given on the course schedule and should be completed before coming to class.
* Assorted handouts, articles, and sample code will be distributed throughout the semester.
* Additional information is also available on the web; do not hesitate to look for further sources of information regarding the concepts, techniques, tools, and paradigms that we will discuss.

==== Materials (must be brought to each class meeting) ====

* 3-ring binder or folder with all course handouts
* Pen, pencil, extra paper
* USB flash drive to back-up data
* Account for this wiki
* [http://www.github.com GitHub account]

=== Course Description ===

The disciplines of biology and computer science come together in bioinformatics, where computational tools are needed to manage and analyze the flood of data coming from new genomics technologies. Biological databases form a significant part of this young and exciting field. This course introduces students to both the biology and computer science expertise needed to understand, use, and develop biological databases. Biology topics include the fundamentals of genetics, molecular biology, and biochemistry needed to understand the data stored in biological databases, as well as the biotechnologies used to gather these data in a high-throughput manner. Computer science topics include what biological databases are, why they are important (and needed), and the challenges that arise in compiling them effectively. Biology and computer science lectures on topics that are relevant to biological databases are coupled with hands-on experience with a variety of software packages ranging from bioinformatics utilities to general-purpose database and software development tools. After learning how to use a biological database, students will be asked to build one of their own.

==== Course Objectives and Learning Outcomes ====

This course is built upon L. Dee Fink’s ''taxonomy of significant learning'', as applied to biological databases. Long after the course concludes, our hope is that:
* You understand how biological information is encoded in the genome and can apply this knowledge to a variety of biological tasks and problems
* You understand the core concepts, structure, and functions of a database, ranging from individual files to a full relational database management system, and can perform useful tasks with such data
* You show discipline and proficiency in day-to-day science and engineering best practices, such as maintaining journals and notebooks, managing your files and code, and critically evaluating scientific and technical information
* You recognize and care about how the biological and technological issues presented in this course relate to and affect society, our daily lives, and ourselves
* You have some skills and tools for “leaving your comfort zone,” flourishing outside of it, and learning more about biology and computer science on your own
* You learn how to communicate and work effectively with colleagues from your discipline and different disciplines

==== University Core Curriculum ====

This course fulfills the following requirements in the University Core Curriculum:
* Integrations: Interdisciplinary Connections

=== Course Work and Grading ===

Your work in this course will be assessed in the following areas:

{| style="border: 1px dashed rgb(47, 111, 171); background: rgb(249, 249, 249); margin: 1em 0; padding: 1em" cellpadding="5ex"
| Weekly electronic lab notebook/journal assignments, individual (usually 12 points each)
| style="text-align: right" | 168 
| points
|-
| Weekly electronic lab notebook/journal assignments, shared (usually 3 points each)
| style="text-align: right" | 42 
| points
|-
| Oral presentations (3 @ 35, 45, 60 points)
| style="text-align: right" | 140
| points 
|-
| Final Project Deliverables (including written report)
| style="text-align: right" | 100
| points
|-
| '''Total'''
| style="text-align: right" | '''450''' 
| '''points'''
|}

Final course grading scale:
94.0-100.0% A
90.0- 93.9% A-
86.0- 89.9% B+
82.0- 85.9% B
78.0- 81.9% B-
74.0- 77.9% C+
70.0- 73.9% C
67.0- 69.9% C-
60.0- 66.9% D
≤ 59.9% F

Current grades will be made available at [http://brightspace.lmu.edu Brightspace].

==== Electronic Laboratory Notebook/Journal ====

One of the most important skills you can develop as a scientist is keeping an excellent laboratory notebook. For computational research, the equivalent of the biology paper-based lab notebook is documentation of your “workflow.” For this course you will practice documentation skills by keeping an electronic lab notebook or journal. The technology we will use is this wiki that we will create and edit during the semester. The wiki software is the same one that runs Wikipedia and many other wiki sites, so proficiency gained here is easily transferable to other applications.

You will create an individual user page and make weekly entries that the instructor will read and grade. You will use the wiki to complete the assignments as well. The following guidelines apply:
* Your weekly journal entry is typically due every 12:01am on Thursday Pacific time; consult the schedule for specific due dates for each assignment.
* Each weekly assignment has an individual component and a shared component. You will earn 12 points per weekly submission for the individual journal entry and 3 points per submission for the shared journal entry. '''''Late journal entries will be accepted up to one week later for up to half credit.'''''
* The instructor will read and comment on how to improve your journal entries on your user talk pages.
* Depending on the type of assignment for that week, you may be given the opportunity to make improvements to previous journal entries as the semester progresses.
* For most weeks in the semester, you will be assigned a "homework partner". You will be expected to consult with your partner in order to complete the assignment. However, unless otherwise stated, each partner must submit his or her own work as the individual journal entry (direct copies of each other's work is not allowed).
* Generally, your journal entries will consist of:
** Your electronic laboratory notebook (workflow and other documentation) for hands-on exercises and projects
** Answers to any specific questions posed in the exercise
** Acknowledgments section (see [[Week 1]] assignment for details)
** References section (see [[Week 1]] assignment for details)
** Shared reflection on your learning, assigned readings, or ethics case studies.

==== Oral Presentations ====

You will give three oral presentations in this course. The first two will be in the format of a “Journal Club” presentation where students will present and lead discussion of research articles from the primary literature. The third will be a research presentation on your final project. '''''Because that day’s class content is dependent upon each student being ready to present and lead discussion, late journal club presentations will not be accepted. An unexcused absence from a journal club presentation will result in a grade of zero for the presentation.'''''

==== Final Group Project ====



In addition to the research presentation, the culmination of your final project will be the preparation of a written laboratory report in the style of a manuscript that could be submitted to a peer-reviewed journal. Specific instructions will be posted later in the semester. '''''The Final Written Report cannot be accepted any later than Friday, May 3 at 12:00pm. The Final Written Report must be completed to receive a passing grade in the course.'''''

==== Life happens, what do I do then? Use your tokens! ====

To succeed in this course it is important to come to each class session and keep up with the work. However, I understand that circumstances may arise from time-to-time that could interfere with this. To responsibly manage these circumstances, the following token system is in place.

* Each student begins the semester with 4 tokens that can be used as follows:
** 1 token = turning in a individual journal entry up to one week later without penalty '''''or''''' dropping a missed shared journal entry from the final grade without penalty.
** 3 tokens = dropping a missed individual journal club entry from the final grade without penalty.
** 4 tokens = excusing an absence without penalty beyond the two automatically excused.
* To use tokens, the instructor must be emailed about your intention to use the token(s) at the day/time of usage (due date or absence). Requests to use tokens after one week from the due date or absence has passed will not be honored. Unused tokens have no point value.
* Up to two additional tokens may be earned by attending extra credit seminars (see below).

==== Extra Credit ====

Students may accumulate up to 12.5 points toward their final grade in extra credit by attending Biology Department seminars and completing the seminar sheets. Each seminar attended is worth 2.5 points with up to 5 seminars (12.5 points) total.

Alternately, you may elect to earn a token for attending the seminar instead of the extra credit points. Only two tokens may be earned this way, and the instructor must be notified of your intention to earn a token instead of extra credit at the time of the seminar by writing it on the seminar sheet on the day of the seminar.

Certain non-Biology Department seminars may be approved in advance for extra credit at the instructor's discretion. To receive credit for these seminars, you must turn in a one-page '''''hard copy''''' of your summary of the seminar '''''in class, within one week''''' of the date of the seminar or they will not count as extra credit.

===== Biology Department Seminar Attendance Policy =====

* To receive course credit for attending a Biology Department Seminar, students must do the following:
** Arrive early at the seminar venue (usually FEA auditorium) and obtain a paper seminar sheet from a faculty member.
*** Seminar sheets will only be available until 3:05 PM, at which time no further sheets will be distributed.
*** You must pick up the seminar sheet yourself. You may not obtain seminar sheets for others.
** Completely fill out the seminar sheet during the seminar, including:
*** Your name as it appears on PROWL
*** All course numbers, section numbers, professor and TA names for the courses for which you would like to receive credit
*** Day and time of seminar, speaker name, and title
*** Answer the other questions on the seminar sheet.
** Stay quietly in your seat for the entire seminar, including the question and answer period.
** At the end of the seminar, take a picture of the seminar sheet and upload it to the survey link accessed via a posted QR code.
** Turn in the paper seminar sheet to a faculty member before exiting the room.
*** You must turn in your own seminar sheet; you may not turn it in for someone else.
* Note that students arriving after 3:05 PM will not receive a seminar sheet and must enter through the back entrance on the second floor of the FEA auditorium so as not to disturb the seminar in progress.

=== Work Load Expectations ===

In line with [https://academics.lmu.edu/media/lmuacademics/provost/documents/LMU%20Credit%20Hour%20Policy_Final.pdf LMU’s Credit Hour Policy], the work load expectation for this course is that for every one hour (50 minutes) of classroom instruction, you will complete a minimum of two hours of out-of-class student work each week. This is a 3-unit course with 3 hours (150 minutes) of instruction per week. Thus the expectation is that you will complete 6 hours of work outside of class per week.

=== University Policy on Academic Honesty ===

Loyola Marymount University is a community dedicated to academic excellence. Academic honesty in scholarship and creative work stands at the center of LMU's academic life, and is essential for true learning and creation of knowledge to take place. As a university in the Jesuit and Marymount traditions, this community expects its members to act in accordance with the highest standards of honesty and ethics at all times. Violations of academic honesty undermine the fundamental educational mission of the University and cannot be tolerated.

Academic dishonesty will be treated as an extremely serious matter with severe consequences. '''''The minimum penalty for an instance of academic dishonesty in this course, even on a 1-point assignment or extra credit assignment, is a one-letter grade penalty in the course and a zero on the assignment.''''' It is never permissible to turn in any work that has not been authored by the student, such as work that has been copied from another student or copied from a source (including the Internet) without properly acknowledging the source. Note that students may not submit assignment or paper prompts to CourseHero, Chegg, online artificial intelligence tools, or any other such website; answers or papers derived from such sites are considered to be a direct violation of the Academic Honesty policy. It is the student's responsibility to make sure that your work meets the standard set forth in the “Academic Honesty Policy” (see http://academics.lmu.edu/honesty.) You are responsible for contacting the instructor before assignments are due to proactively resolve any questions you may have.

You are required to sign the [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]] for this course.

==== Academic Honesty Resources ====
* [[Media:BIOL367_Spring2024_AcademicHonestyAgreement.pdf|Academic Honesty Agreement]]
* [https://academics.lmu.edu/media/lmuacademics/academichonesty/documents/Academic-Honesty-Policy-2021.pdf LMU Academic Honesty Policy and Procedures]
* [http://www.bio.davidson.edu/dept/plagiarism.html The Davidson College Department of Biology Guidelines for Using and Citing Sources]
* [[Media:BIOL367_Spring2024_GuidelinesforLiteratureCitations.pdf | Guidelines for Literature Citations in a Scientific Paper]]
** [https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_basic_rules.html APA Style for References]
* [http://dondi.lmu.build/share/misc/plagiarism.pdf Notes on plagiarism from an electrical engineering & computer science perspective]
* [http://libguides.lmu.edu/BIOL367 BIOL/CMSI 367 LibGuide]

=== Americans with Disabilities Act—Special Accommodations ===

Students with special needs who require reasonable modifications, special assistance, or accommodations in this course should promptly direct their request to the Disability Support Services (DSS) Office. Any student who currently has a documented disability (ADHD, Autism Spectrum Disorder, Learning, Physical, or Psychiatric) needing academic accommodations should contact the DSS Office (Daum Hall 2nd floor, 310-338-4216) as early in the semester as possible. All discussions will remain confidential. Please visit http://www.lmu.edu/dss for additional information. In addition, please schedule an appointment with the instructor early in the semester to discuss any accommodations for this course for which you have been approved.

=== Health and Wellness ===

There are many resources for student wellness on campus. A central website for students is: http://lionwellness.lmu.edu.

==== COVID-19 ====

All University mandated COVID-19 safety guidelines are to be followed. The [https://www.lmu.edu/together/ LMU Together] and [https://www.lmu.edu/together/resources/matrix/ Need to Know A-Z Index] websites contain updated information. If you have COVID-19 symptoms and/or test positive, please contact the COVID Support Team ([mailto:COVIDSupportTeam@lmu.edu COVIDSupportTeam@lmu.edu] or 310-568-6868) for instructions.

=== Emergency Preparedness ===

To report an emergency or suspicious activity, contact the LMU Department of Public Safety by phone (x222 or 310-338-2894) or at the nearest emergency call box. In the event of an evacuation, follow the evacuation signage throughout the building to the designated safe refuge area where you will receive further instruction from Public Safety or a Building Captain. For more safety information and preparedness tips, visit http://www.lmu.edu/emergency.

=== Revision Notice ===

If necessary, this syllabus and its contents are subject to revision; students are responsible for any changes or modifications announced in class. The most current version of this information resides on this page, the course web site at http://xmlpipedb.cs.lmu.edu/biodb/spring2024/.

2024-04-23T16:15:42Z

Kdahlquist: /* Milestone 6: Document the schema and design queries to create the GRNmap input workbook */ add label

Coder/Designer

2024-04-23T16:15:13Z

Kdahlquist: /* Milestone 6: Document the schema and design queries to create the GRNmap input workbook */ add link to sample workbook

File:15-genes 28-edges sample-GRNmap Sigmoid estimation.xlsx

2024-04-23T16:14:47Z

Kdahlquist: sample input GRNmap workbook that the coders can use for testing

== Summary ==
sample input GRNmap workbook that the coders can use for testing

Kdahlquist: /* Milestone 3: Design a database to store data needed to create a GRNmap input workbook */ add link to Harbison data

File:Pvalbygene forpaper abbr.xls

2024-04-11T20:07:26Z

Kdahlquist: Supplemental Data from Harbison et al. (2004)

== Summary ==
Supplemental Data from Harbison et al. (2004)