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Loyola Marymount University

BIOL 367-01: Biological Databases

Fall 2019

Announcements

• Please complete the course evaluation on Brightspace by class time on Thursday.
• Data Analysts and QA's who have a partner in their group 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.

• The combined database may be found here.

Upcoming Seminars

• There are no further seminars.

Instructor

• Kam D. Dahlquist

Students

Michael Armas	Christina Dominguez	Kaitlyn Nguyen	Naomi Tesfaiohannes
Marcus Avila	Ivy-Quynh Macaraeg	John Nimmers-Minor	Emma Young
Jonar Cowan	DeLisa Madere	David Ramirez
Iliana Crespin	Yeabsira Mesfin	Mihir Samdarshi

Final Project Links
Overview	Deliverables	Guilds	Project Manager	Quality Assurance	Data Analysis	Coder/Designer
		Teams	FunGals	Sulfiknights	Skinny Genes

Course 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.

Part 1: Building Blocks (Genetic Code and Manipulating Text)

#	Date	Reading	Agenda	Journal
1	Tuesday 8/27/2019		Syllabus walkthrough Pairwise interviews and introductions Academic Honesty case studies Class wiki account: Set up a username and password for this wiki site	Week 1 (due at 12:01am 9/5) Class Journal Week 1
	Thursday 8/29/2019	Chapter 1 of On Becoming a Biologist by John Janovy, Jr. (on Brightspace) Voices of Computing and Computing is a Natural Science by Peter Denning (these links should be accessed from within LMU to get the full article)	What is a model? Model of a cell/model of a computer Slides on Brightspace
2	Tuesday 9/3/2019		Discuss the Week 1 assignment Wiki syntax overview Lab session to setup User wiki page	Week 2 (due at 12:01am 9/12) Class Journal Week 2
	Thursday 9/5/2019	Ch. 1 Genomes 2 Brown, T.A. (2002) Genomes 2, Ch. 3, especially section 3.3.2 On Brightspace: Nirenberg (2004) Deciphering the Genetic Code Kaji & Kaji (2004) Setting the Record Straight Moody (2004) Digital Code of Life, Ch. 1 Hayes (2004) Ode to the Code	DNA structure Slides on Brightspace
3	Tuesday 9/10/2019		Aipotu work session	Week 3 (due at 12:01am 9/19) Class Journal Week 3
	Thursday 9/12/2019		Genes as models Central model of molecular biology Berkeley translation video This web site has links to animations of the replication, transcription, and translation processes. Slides on Brightspace Paper and pencil exercise
4	Tuesday 9/17/2019	Ford, Paul. “What is Code?” Business Week, June 11, 2015. DataONE: Data Management Slides	Introduction to biological databases (part 1) What is bioinformatics? Open Science Ecosystem DataONE: Data Management and the life cycle of data Slides are on Brightspace	Week 4 (due at 12:01am 9/26) Class Journal Week 4
	Thursday 9/19/2019		Introduction to biological databases (part 2) 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
5	Tuesday 9/24/2019		Week 4 work session	Week 5 (individual due at 12:01am 10/1) Note Tuesday Due Date Class Journal Week 5 (shared due at 12:01am 10/3)
	Thursday 9/26/2019	The 26th annual Nucleic Acids Research database issue The NAR Molecular Biology Database Collection	Introduction to biological databases (part 2) Terminology, types, evaluation, four "Gold Standard" databases A closer look at evaluating biological databases (slides on Brightspace) DataONE: Data Sharing Presentation Guidelines PowerPoint on Brightspace
6	Tuesday 10/1/2019		Database presentations part 1 group 1 group 2 group 3 group 4	Week 6 (due at 12:01am 10/10) Class Journal Week 6
	Thursday 10/3/2019		Database presentations part 2 group 1 group 2 group 3 Presentation Rubric Presentation Guidelines on Brightspace

Part 2: Going Deeper (Gene Expression Data and Relational Databases)

#	Date	Reading	Agenda	Journal
7	Tuesday 10/8/2019	For more on the Human Genome Project, see: Moody (2004) Chapter 6 (on Brightspace) Science After the Sequence Nature Special: Human Genome at 10 Human Genome Project articles in Science Human Genome Project articles in Nature	Human Genome Project to DNA microarrays (slides on Brightspace)	Week 7 (due at 12:01am 10/17) Class Journal Week 7
	Thursday 10/10/2019	Alberts et al. (2002) Molecular Biology of the Cell, Ch. 8: Microarrays Brown & Botstein (1999) "Microarrays" Nature Genetics Campbell & Heyer Chapter 4 (on on Brightspace) DeRisi et al. (1997) Science 278: 680-686.	Review Week 6 assignment
8	Tuesday 10/15/2019	DataONE: Data Entry and Manipulation	More about DNA microarray analysis Slides on Brightspace	Week 8 (due at 12:01am 10/24) Class Journal Week 8
	Thursday 10/17/2019		Begin DNA microarray analysis part 1 Statistical analysis of Dahlquist Lab yeast cold shock dataset Test your understanding: http://xkcd.com/882/
9	Tuesday 10/22/2019	Ernst & Bar-Joseph (2006) STEM: a tool for the analysis of short time series gene expression data.	Microarray Data Analysis part 2 Clustering with stem software	Week 9 (due at 12:01am 10/31) Class Journal Week 9
	Thursday 10/24/2019	Teixeira, et al. (2017). YEASTRACT: an upgraded database for the analysis of transcription regulatory networks in Saccharomyces cerevisiae Dahlquist et al. (2016) GRNsight: a web application and service for visualizing models of small- to medium-scale gene regulatory networks	Microarray Data Analysis part 3 Finding a candidate GRN (YEASTRACT)
10	Tuesday 10/29/2019	Dahlquist et al. (2015) Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae	Microarray Data Analysis part 4 Visualizing the candidate GRN (GRNsight) Dynamical systems modeling of the gene regulatory network (GRNmap)	Week 10 (due at 12:01am 11/7) Class Journal Week 10
	Thursday 10/31/2019		Microarray Data Analysis part 5 Visualizing and interpreting the modeling results (GRNsight) Group requests due in class (collected on notecards)

Part 3: Integrating for Research (GRNsight Gene Expression Database Project)

#	Date	Reading	Agenda	Journal
11	Tuesday 11/5/2019		Dynamical Systems Modeling with GRNmap	Week 11 (due at 12:01am 11/14) Thursday Due Date
	Thursday 11/7/2019		Begin GRNsight Expression Database Project Team assignments Overview of project Work session to create Team wiki pages
12	Tuesday 11/12/2019		Literature searching and annotated bibliographies Course LibGuide: http://libguides.lmu.edu/BIOL367 Select microarray papers for journal club	Week 12/13 (due at 12:01am 11/26) Note Tuesday Due Date
	Thursday 11/14/2019		Journal Club Presentations Presentation Rubric Presentation Guidelines PowerPoint on Brightspace
13	Tuesday 11/19/2019		Status report Work session	Week 12/13 (due at 12:01am 11/26) Note Tuesday due date
	Thursday 11/21/2019		Status report Work session
14	Tuesday 11/26/2017		Status report Work session	No Week 14 assignment
	Thursday 11/28/2019		Thanksgiving—no class
15	Tuesday 12/3/2019		Status report Work session	Week 15 (due at 4:00pm 12/13)
	Thursday 12/5/2019		Status report Work session
F	Tuesday 12/10/2019		Final project presentations 2:00-4:00 PM
	Friday 12/13/2019 4:00 PM		Project deliverables due 4:00 PM

Course Information

Instructor

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 (Fall 2019): Mondays & Wednesdays 2:00-3:00 PM, Tuesdays & Thursdays 4:00-5:00 PM, and by appointment; I keep a sign-up sheet next to my office door to facilitate appointment-making.

Prerequisites/Recommended Background

To take this course, you must have upper division standing in the Seaver College of Science and Engineering. Otherwise, there are no strict prerequisites. Backgrounds in biology and computer science, as well as prior experience with web, database, or information management applications, may be helpful but not necessary.

Class Meetings and Attendance

TR 2:40–3:55pm, 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 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 August 30. The withdrawal or credit/no-credit status deadline is November 1.

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:

1. As an LMU Lion, by the 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.
2. You are responsible for your own learning and for being a good class citizen.
3. Class will start promptly on time.
4. 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.
5. You are expected to bring the required materials to each class session.
6. 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.
7. All students are governed by LMU Community Standards publication. 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/fall2019/. 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 Brightspace. The site will be used for materials that cannot be made public on this wiki, including grades.

Email Communication

At times we 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 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 with all course handouts
• Pen, pencil, extra paper
• USB flash drive to store data
• Account for this wiki
• 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 different disciplines

University Core Curriculum

This course fulfills the following requirements in the University Core Curriculum:

• Integrations: Interdisciplinary Connections
• Upper Division Information Literacy Flag
• Upper Division Oral Communication Flag

Course Work and Grading

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

Weekly electronic lab notebook/journal assignments, individual (usually 10 points each)	155	points
Weekly electronic lab notebook/journal assignments, shared (usually 3 points each)	43	points
Oral presentations	120	points
Final Project Deliverables (including written report)	100	points
Total	418	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 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. 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 10 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, December 13 at 4:00pm. The Final Written Report must be completed to receive a passing grade in the course.

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. You must attend the entire seminar from start to finish and personally turn in your seminar sheet to a faculty member at the end 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.

Work Load Expectations

In line with 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 Internet) without properly acknowledging the source. 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 Academic Honesty Agreement for this course.

Academic Honesty Resources

• Academic Honesty Agreement
• LMU Academic Honesty Policy and Procedures
• The Davidson College Department of Biology Statement on Plagiarism
• Guidelines for Literature Citations in a Scientific Paper
  • APA Style for References
• Notes on plagiarism from an electrical engineering & computer science perspective
• 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.

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/fall2019/.