Revision as of 04:21, 10 September 2017

Mary Balducci's Respones

1. The biggest discovery that I made while doing these readings was that there was so much similarity between the genetic code and computer code. I've taken biology courses before, so I knew that DNA worked using four letters that coded for proteins. However, I've never taken a computer science course so I never really understood how computer coding worked. It was interesting to read the connections made in the Digital Code of Life between the two. I think this has also given me a better understanding of computer coding, since I can relate it to something I already know about.
2. The thing I understood least from these readings was at the end of the Ode to the Code article. Hayes talks about the fact that there are 64 codons, but only 20 amino acids. One of the proposals for the organization of these is the 2x2x2x2x2x2 hypercube. I am confused about what this would look like, and how does it get across information differently than the 4x4x4 cube currently in use?
3. The genetic code and computer code are similar because they both code digitally. By doing this, there are less mistakes made between the information and the copy of the information. Both types of codes work by having letters or numbers that convey a meaning that the computer or cell carries out.

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Page DesiignerMbalducc (talk) 18:15, 6 September 2017 (PDT)

Katie Wright's Responses

1. My biggest discovery from the reading was that even brilliant scientists can make mistakes and need to be corrected. I thought the communication by Kanji and Kanji about "setting the record straight" was interesting because, had I not seen it, I would have read the autobiographical paper by Nirenberg without questioning it. I suppose it is a reminder that we should question and be critical of all science, regardless of who it is presented by.
2. I understood the readings pretty well for the most part, although I did skim through some of the biology that Nirenberg describes in his autobiographical story. I tried to focus more on the narrative than the science, since I know the basics already from my previous classes.
3. The genetic code is incredibly similar to computer code. As Glyn Moody demonstrates in his book, the genetic code can easily be converted to binary, which is one of the most important types of computer code. Since the genetic code can be easily digitized, we can use a wide array of computer programs to study the genetic code that would not be available in non-digital systems.
   Kwrigh35 (talk) 21:00, 9 September 2017 (PDT)

Zachary Van Ysseldyk's Responses

1. The biggest discovery I made from these readings was from the Digital Code of Life reading. Specifically, when they compared DNA’s ATCG pairings with the computer’s 0 and 1 binary code. What I found interesting was that both ATCG and binary are representations of something rather than the actual property themselves. I also realized how much computers helped with mapping out DNA considering how large the human genome is. Furthermore, I discovered that both biology and coding have a very systematic approach. I always thought biology was arbitrarily observing living cells and seeing if they can find a connection. With the introduction of bioinformatics, a clear systematic approach becomes clear when it comes to biology.
2. The deciphering of the genetic code was probably the most academic and confusing paper I have ever read in my life. I have never had to look up so many words in a sentence. The phrase: “in the presence of a high concentration of methanol, pancreatic RNase A catalyzes the synthesis of trinucleotides and higher homologues from oligoribonucleotide primers and pyrimidine 2’-3’-cyclic phosphates” was probably the most confusing sentence I have read. The last time I took biology was freshman year of high school so I really felt like I dove in head first here.
3. Similar to my answer to question 1, I think that the biggest relationship between genetic and computer code is how the actual coding is a mere representation of what the data actually is. Also, both codes must be very exact and precise. If there is an error, then the entire code will spew out something other than what was intended.

Zvanysse

BIOL/CMSI 367-01: Biological Databases Fall 2017

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