BIOL398-03/S13:Class Journal Week 12

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Revision as of 15:09, 10 April 2013 by Matthew E. Jurek (talk | contribs) (Matthew E. Jurek Week 12: working on response)
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Kevin McKay

  • After last weeks excel assignment, the excel work came easiest to me this time.
  • Most challenging was making the connection between genes and why they were regulated differently during cold shock.
  • I do not fully understand the connections between the cluster I had and the cold shock, further testing may help me out a bit when we make the model.
  • Per gene p values told us if an individual gene was regulated at a statistically significant level during cold shock in the yeast, and the same goes for the clusters and the GO terms. If the p value is less than .05, then we had a statistically significant piece of data to work with, or something worth looking into.

Kevin Matthew McKay 20:15, 9 April 2013 (EDT)

Matthew E. Jurek Week 12

Matthew E. Jurek

  1. What aspect of this assignment came most easily to you?
    • Since we were working with two computer programs I've never used before, I'd say manipulating the Excel spreadsheets was the easiest. Before inputing data into STEM and the database, the excel spreadsheets had to be modified. We've worked with Excel multiple times before, and these modifications consisted of simple tasks like deleted rows or copying and pasting.
  2. What aspect of this assignment was the most challenging for you?
    • Working with STEM was the most challenging step. Our data started in Excel but had to be modified before being input into Excel. The command window itself had a lot of different options. Luckily the instructions were very easy to follow. After running STEM, a screenshot was saved to powerpoint, then the GO term and gene lists had to be saved as different files. All of this had to be uploaded to lionshare with special permission for Dr. Dahlquist
  3. What (yet) do you not understand?
  4. For the week 9 and 12 assignments we computed (or the software did) three different p values: per individual gene, per profile, and per Gene Ontology term. State in your own words what we need each of these p values for and what are they telling us?