User talk:Kristen M. Horstmann

Week 11 Feedback Part 2

• 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 your stem results:
    • Half of your profiles show an "up then down" pattern and the other half show a "down than up" pattern. Slightly more genes have the former profile, but on the whole, it's roughly half and half.
    • In terms of the GO results, 1, 3, 6, 7, 8,and 9 and possibly 5, all have to do with amino acid biosynthesis. It seems that the cold shock is somehow making the cell limited for amino acids and they are responding by upping the biosynthesis. Recall from the first half of the course that glutamine synthesis is part of central nitrogen metabolism, so your results connect with that. Maybe because the cell membranes stiffen with cold, the cell can't take up amino acids from the environment as easily and have to start to manufacture their own.
    • You have both "negative regulation of cellular macromolecule biosynthetic process" and "positive regulation of macromolecule metabolic process" in your list. I think that all that can be concluded from this is that the cell is changing the regulation of its macromolecules in response to stress, up-regulating some and down-regulating others. This is probably connected to "response to stress". Cold shock is an environmental stress that the cell has to overcome to maintain homeostasis as you state.

— Kam D. Dahlquist 19:25, 4 May 2015 (EDT)

GRNsight

• The GRNsight home page has been fixed and is now working. — Kam D. Dahlquist 18:51, 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?
    • Your answer to this question is actually a better answer to the second question above. Here we are talking about comparing the weight and production rate values in your bar charts. 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, the main difference is for MIG2 between the two runs. MSN2 also shows a difference. How will you explain this result? Also, when comparing your data with Kara'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.
• Please make the changes requested to your spreadsheet and make sure to update your Week 13 electronic notebook with what you changes.
• Your electronic notebook looks to be purely a copy and paste of the assignment protocol, with some specific data recorded at the bottom. You need to modify the protocol text itself with the changes specific to what you did, instead of listing it separately.
  • Link to your own individual assignment pages throughout the protocol when it refers to data coming from previous assignments.
  • Give the filename for your new file, as well as the link.
  • Record the changes you made to the "optimization_parameters" sheet.

— Kam D. Dahlquist 18:50, 21 April 2015 (EDT)

Week 11 Feedback Part 1

• I checked your spreadsheet and all of your equations are correct!

— Kam D. Dahlquist 01:06, 26 March 2015 (EDT)

Week 7 Feedback

• Your Week 7 individual journal assignment and shared journal reflection were both 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. In addition to your MATLAB files, you need a complete 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 13:00, 17 March 2015 (EDT)

Week 1 Redux

• I reviewed your Week 1 assignment a second time and noted that you made no further changes to this assignment.
• I note that your usage of the summary field is still excellent; you have written comments in the summary field for 99% of the last 50 contributions you made. Keep up the good work.

— Kam D. Dahlquist 19:24, 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).
  • You are doing a very good job of typing something in the summary field every time you make a change to the wiki--keep up the good work.
  • Your external link needs a label on the link.
  • 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.
  • Please "comment out" a section of your code. You did not make any comments that weren't already put there by the automated page creator.
  • You can also remove the OpenWetWare automated text from the bottom of this talk page.

— Kam D. Dahlquist 17:39, 29 January 2015 (EST)

I've answered your question on my User talk page. — Kam D. Dahlquist 21:28, 29 January 2015 (EST)

Answer to question from Dr. Fitzpatrick

You asked Is there any aspect of math that you dislike doing?

Nope. I like pretty much all of it as I encounter it. There is still a lot to learn, even after 30 years in the business. Ben G. Fitzpatrick 01:16, 21 January 2015 (EST)