User talk:Kara M Dismuke

Week 11 Feedback

• I have some observations to make about your Week 11 assignment as you prepare for the final paper/presentation.
  • With regards to the table with your ANOVA results, the table and data look good. You will need to shorten your title for this slide so that it fits onto 2 lines. It is preferable not to say "Table X" or "Figure X" as part of the title of a PowerPoint slide, although you would do this as a legend for your paper. Also, do not use the word "prove" except in the context of an actual mathematical proof. You can use words like "show" or "demonstrate" instead.
  • With regards to the stem results, note that the y axes on the profile plots are not all the same. The y axis for profiles 45 and 22 goes up to a log fold change of 20, which is quite large! The other profiles go up to 4 or 5 which is actually still large in terms of gene expression terms, but is more reasonable to expect. Because profile 54 and 22 have such a large range for their y axes, it makes it appear that most genes are not changing that much, but they actually are. We would consider a log2 fold change of >.25 or < -0.25 to be meaningful, and most genes in those clusters actually do so. Remember those clusters are entirely composed of genes whose ANOVA p value was < 0.05 so they had to have a log fold change significantly different than zero at at least one timepoint.
  • Also with regards to your paragraph interpreting your GO results, you do not really discuss your GO results at all.
    • Terms 1, 3, 4, 5, and 9 in your list all have to do with ribosome biogenesis, the process of making new ribosomes. This is a "classic" response to cold shock by the cell. Cold temperatures stabilize RNA secondary structures. The ribosome is composed mostly of RNA and when the structure is stabilized, it gets "stuck" and cannot perform translation very well. Thus, the cell responds by making more ribosomes to compensate.
    • Terms 2 and 7 in your list have to do with transfer RNA, the molecules that bring amino acids to the ribosome to make proteins. It seems that the cell is not only making more ribosomes, but also making more tRNAs too, to deal with the problem noted above.
    • Terms 6 and 8 in your list are very broad terms because they refer to any membrane-bound organelle, of which there are several in the cell. It might be better to dump these two terms in favor of some other two that are more specific and thus easier to interpret.
    • Term 10 is also very broad since it applies to many different molecules in the cell.

— Kam D. Dahlquist 18:28, 4 May 2015 (EDT)

GRNsight

• The GRNsight home page has been fixed and is now working. — Kam D. Dahlquist 18:50, 30 April 2015 (EDT)

Week 14 Feedback

• I have some observations to make about your data as you prepare for the final paper/presentation (I'm copying both partners on this feedback).
  • Which genes in the model have the closest fit between the model data and actual data? Why do you think that is? How does this help you to interpret the microarray data?
    • I agree that CYC8 has good fit, but I would dispute that the fit to the SWI5 data is better than some other genes. The model at t15 is only hitting the topmost replicate of the data for t15. For other genes, it seems to pass through the average much better for all of the timepoints. CYC8 probably does have the smallest difference between replicate datapoints. It is also not changing it's expression. The average of all the timepoints goes through 0 log fold change. There does seem to be a relationship between goodness of fit and noise in the data.
  • Which genes showed the largest dynamics over the timecourse? Which genes showed differences in dynamics between the wild type and the other strain your group is using? Given the connections in your network (see the visualization in GRNsight), does this make sense? Why or why not?
    • When we are talking the "largest dynamics" over the timecourse, it means which genes showed the largest changes in expression (non-zero log fold changes) at any timepoint and between timepoints. I agree that YLR278C does show fairly large dynamics, but PDR1 and RIF1 are pretty close to zero throughout the timecourse. CIN5, HMO1, MIG2, YOX1, and ZAP1 (for wt data) all show larger difference from zero (mainly upward trends). Your ACE2 results make sense with regard to the structure of your network.
  • Examine the bar charts comparing the weights and production rates between the two runs. Were there any major differences between the two runs? Why do you think that was? Given the connections in your network (see the visualization in GRNsight), does this make sense? Why or why not?
    • What I see in your comparison of the weights between the fixed and estimated b runs is that almost all of the weights track very closely except for the following:
      • MSN2-->MIG2, the weight with the estimated be is somewhat larger.
      • MIG2-->RIF1, the weight changes sign between the two runs, but the magnitudes are pretty small.
      • CIN5-->MIG2, the sign changes between the two runs with very large magnitude difference. This is the most dramatic difference between your runs.
      • HMO1-->MSN2, change in sign, but very small magnitude.
      • HMO1-->HMO1, change in sign, but small magnitude.
    • You'll want to think about how to explain the differences you see, especially for CIN5-->MIG2.
    • In terms of the production rates, how will you explain the changes you see? Also, when comparing your data with Kristen's, the bar charts for the weights track with each other, but you seem to have different results for the production rates.
  • As you prepare for your final presentation and paper, think about how you will display the graphs in your talk. You will probably want to focus in on the genes that illustrate points about the fit, dynamics, differences between the fixed b and estimated b runs, and the differences between genes. You will want to put graphs for the same gene next to each other on the same slide so that they can be easily compared. Also, it might be helpful to arrange genes in alphabetical order on everything to facilitate reading the data. Note that you don not need to do any additional Matlab runs to accomplish this, you can rearrange your bar charts in Excel and organize your graphs in PowerPoint.
  • Make sure that the titles of your slides convey a "message" or "result", not just the topic of the slide.

— Kam D. Dahlquist 17:01, 30 April 2015 (EDT)

Week 13 Feedback

• Thank you for submitting your work on time.
• When you make the requested changes to your spreadsheet, make sure to make corrections to your electronic notebook for the Week 13 assignment as well.
• Your electronic notebook is excellent. Keep up the good work.

— Kam D. Dahlquist 19:02, 21 April 2015 (EDT)

Week 11 Feedback Part 1

• I looked over your spreadsheet and you need to make the following corrections:
  • You have a mistake in the equation for column P, you use the number "2" instead of the reference to cell "O2"
  • You did not perform the Bonferroni correction in column R or the IF statement in column S.
  • It is customary to use a "d" in front of "ZAP1" in your column headers to indicate that ZAP1 is deleted from that strain. Ordinarily we would use a delta to mean deleted, but that special character would mess up things downstream in the analysis, so we use a "d". Please put it in your column headers.

— Kam D. Dahlquist 02:36, 26 March 2015 (EDT)

Week 7 Feedback

• Your Week 7 individual journal assignment was late by 29 minutes and your shared journal reflection was on time.
• You fulfilled all of the hyperlinks required for the assignment (back and forth to user page, to assignment, category).
• Your electronic notebook is minimal. The intent of an electronic notebook is to record what you did so that you or somebody else could reproduce what you did based on the information there. You needed to provide your MATLAB files, a description of what values you used for each run of the model and why you chose them, and the the resulting plots and your interpretation of what they mean. You only commented on how you worked with your partner, not what you actually did for the analysis.
• You needed to perform an analysis of the steady state.

— Kam D. Dahlquist 12:57, 17 March 2015 (EDT)

Week 1 Redux

• I have reviewed the changes you made to the Week 1 assignment; thank you for submitting them on time.
• You made all of the requested changes, but I note that your usage of the summary field has dropped slightly from about 90% in the first assignment to 78% of the last 50 contributions. Remember that you should also write a summary for all files uploaded to the wiki.

— Kam D. Dahlquist 19:57, 10 February 2015 (EST)

Week 1 Feedback

Here is the feedback to your Week 1 journal assignment.

• Thank you for completing this assignment on time.
• The grade for this assignment is posted on the MyLMUConnect Grade Center for this course. You will be able to earn back the points you missed on this assignment by completing the requested revisions below by the Week 3 journal assignment deadline of midnight on Tuesday, February 3 (Monday night/Tuesday morning).
  • Every time you make a change to a wiki page, please type something in the summary field (found above the "Save page" button). You are doing this approximately 90% of the time, but you should aim for 100%.
  • The OpenWetWare e-mail link does not actually work (try it to see what I mean). Either fix this or make a "mailto" link to your e-mail address.
  • Under your section on "Work Experience", you did not provide the terms for your presidency/vice presidency of the Belles.
  • You did not use and "third" level subheadings (three equals signs or more). Be sure to utilize this feature to organize content on your journal pages.
  • You can also remove the OpenWetWare automated text from the bottom of this talk page.

— Kam D. Dahlquist 16:24, 29 January 2015 (EST)

I've answered your question on my User talk page. — Kam D. Dahlquist 21:26, 29 January 2015 (EST)

Answer from Dr. Fitzpatrick

You asked What are your favorite movies (top three)?

1. Field of Dreams
2. The Big Lebowski
3. Brazil

Ben G. Fitzpatrick 01:13, 21 January 2015 (EST)