User talk:Tessa A. Morris

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Week 11 Part 2

  • I have some observations to make about your Week 11 assignment as you prepare for the final paper/presentation.
    • With regard to your stem results:
      • All of the terms 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. Make sure you understand why I say that all of these terms are referring in some way to ribosome biogenesis and if you don't, please let me know.
      • Also, remember that the three cold shock timepoints are t15, t30, and t60. t90 and t120 are the recovery from cold shock back at 30 degrees C.
    • Double check the number you reported for the unadjusted p value for NSR1; it is the same as your Bonferroni-corrected p value and both of them should be <1.
    • There appears to also be an error in the ANOVA table in your PowerPoint. You are reporting the same percentage for p < 0.0001 and the B-H p < 0.05. Also, please give the actual number of genes for each of the p values as well as the percentages in your table.

Kam D. Dahlquist 13:13, 5 May 2015 (EDT)


  • 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).
  • Since you re-did your runs in class today, you don't have an interpretation of your data on your Week 14 page that actually matches your new data. Here are some observations that I have made.
    • 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?
      • There does seem to be a relationship between goodness of fit and noise in the data. In fact, instead of talking about which genes have a particularly good fit, there seems to be some ones that have a particularly bad fit, like MIG2. Also there seems to be a few cases where the data for the wt and dGLN3 strain diverge quite dramatically, but the model does not and therefore does not fit the individual strain data very well, like STB5, YHP1, YOX1, and ZAP1.
    • 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. When I look at your graphs, it seems that CIN5, HMO1, INO4, MIG2, MSN4, PDR1, SFP1, SNF5, and YLR278C all show non-zero dynamics in terms of the model. As noted above, some of the model fits aren't very good and the data are actually showing some dynamics that the model is not capturing. How do you explain this?
    • 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 weights and production rates from the two runs are very similar to each other, as you expect because GLN3 is not actually controlling any other genes in the network. But as we noted above, the model does not seem to be capturing the dynamics of the differences between strains. How do you explain this?
    • 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. I like how you have put graphs for the same gene next to each other on the same slide so that they can be easily compared. Note that on your bar chart that compares the weights, only half of the labels are showing on the x axis. You might need to break this up into two charts so that those can be read.
    • Make sure that the titles of your slides convey a "message" or "result", not just the topic of the slide.

Kam D. Dahlquist 18:00, 30 April 2015 (EDT)

Week 13 Feedback

  • Thank you for submitting your work on time.
  • I have confirmed that you made the fixes requested to your spreadsheet. Please make sure to go back and correct your Week 13 electronic notebook to reflect these changes.
  • Your electronic notebook is good, but could be improved by the following:
    • Don't forget to say the file extension when reporting the names of files; it is part of the filename, too.
    • When reporting which transcription factors you needed to substitute the given value of the degradation rate, record this information at the place it appears in the protocol, not in a separate place.
    • Make sure to record the changes you made to the "optimization_parameters" sheet in the appropriate place in the protocol.
    • Link to your own Week 11 page in the appropriate place in the protocol.

Kam D. Dahlquist 18:45, 21 April 2015 (EDT)

Week 11 Feedback Part 1

  • I checked your spreadsheet and all of the equations are correct. However you did the Bonferroni correction when the filter was applied so the equation did not copy to all of the rows. You also need a column header for Column S.

Kam D. Dahlquist 01:35, 26 March 2015 (EDT)

Week 7 Feedback

  • Your Week 7 individual and shared journal assignments 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 was 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. Your notebook was only a description of how you and Alyssa worked together, with very little detail of what you actually did in terms of the modeling. In addition to the MATLAB files, you should have described what values you used for each run of the model and why you chose them. In addition to the plots, you needed to interpret what they mean.
  • You needed to perform an analysis of the steady state.

Kam D. Dahlquist 13:09, 17 March 2015 (EDT)

Week 1 Redux

  • I have reviewed the changes you made to the Week 1 assignment. You have made all of the changes requested by the deadline. You have also made comments in the summary field for 100% of the last 50 contributions; keep up the good work!

Kam D. Dahlquist 19:43, 10 February 2015 (EST)

Week 1 Feedback

Here is the feedback to your Week 1 journal assignment.

  • Thank you for submitting your Week 1 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 each time you make a change to the wiki--keep up the good work.
    • 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 wiki code.
    • Please remember to sign your comment on the shared class journal page with your wiki signature ~~~~.
    • The file you uploaded to the wiki is just named "CV". Many users could potentially upload a file with this name and overwrite your file. It is good practice to include your username (and the date) in every file you upload to the wiki to make sure that your filename is unique.
    • I can see that you modeled your template after the main template for the course. Your template looks good, but does not have quite the information that I intended for student templates. I would like your template to contain a list of links to the Assignment pages, a list of links to your individual journal entries, and a list of links to the shared journal entries, as well as a link to your user page and the BIOL398-04/S15 category. I would prefer all of this information appear on your actual user page (and in subsequent weeks on your individual journal pages as well) and not on a separate page. The reason for this is that it helps me navigate the wiki while I am grading all 10 students' assignments. Having to go to an extra page takes additional time when I could just go there directly. You can still keep the header in place, but provide these links elsewhere on the page. Let me know if you need assistance formatting this.
    • You can also remove the OpenWetWare automated text from the bottom of this talk page.

Kam D. Dahlquist 17:56, 29 January 2015 (EST)

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

Answer from Dr. Fitzpatrick

You asked What is the course you like teaching the least and why?

When I was a master's student, teaching business calculus was part of the reason I left grad school to work in industry. The students whined and complained about everything. They treated every grade as an opportunity to negotiate, a process I really came to dread. I'm older now, with thicker skin, and such things don't bother me so much. Teaching precalculus is hard, because I never saw anything difficult about it. Helping students through hard material is easier if the teacher can understand what about it confuses the students. From calculus up, I can at least have some empathy for student difficulties, but below that it's tough for me to connect. Ben G. Fitzpatrick 01:43, 21 January 2015 (EST)