User talk:Natalie Williams
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:
- Terms 1, 3, 4, 5, 6, 8, 9, and 10 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. If it is not obvious to you why I say all of these terms are basically referring to the same thing, let me know.
- Term 7, nucleoplasm, excludes the nucleolus where ribosome biogenesis takes place and probably refers to other gene expression changes happening.
- Term 2, hexose transport is really the only really different one in this list. Apparently during cold conditions, the cell needs to up-regulated sugar transporters, to possibly take in more energy and/or carbon sources.
- With regard to your stem results:
— Kam D. Dahlquist 20:00, 4 May 2015 (EDT)
Week 14 Feedback
- I have some observations to make about your data as you prepare for the final paper/presentation.
- 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?
- It might be better to flip this question and say which genes did not have a good fit. All of the genes seem to have a pretty good fit except for INO4, MIG2, and MSN2. You claimed that the fit for MIG2 is good, but even though there is the uptick at t15, the model does not actually pass through the average of the points. MSN2 has a weird peak before the t15 timepoint and INO4 has an upward trend in the data, but a downward trend in the model. There does seem to be some relationship between variability in the data and goodness of fit.
- 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?
- MIG2, MCM2, INO4, MGA2, ZAP1, MSN4, CIN5, STB5, YHP1, YOX1, FKH2, YLR278C all show nonzero dynamics in the data. Does this make sense given the connections in the 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?
- Agreed, in the run with both strains, there are few differences in the weight and production rate terms between runs.
- 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 strains. 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.
- I noticed on your bar chart for the weights that the labels on the x axis are not all showing up. You might need to split this into two charts for them to show.
- For your slide showing the percentages of genes meeting the various p value cut-offs, you need to report the actual number, not just the percentage. For example, like this: 300 (4.8%). I would not make too much out of the differences in percentages, they are only off by a little bit. This probably has more to do with the variance in the wild type data (which is higher) than anything particularly special about S. paradoxus. Also, your title for this slide is awkwardly phrased. What you are reporting has nothing to do with the NSR1 gene.
- For your clusters, double-check that the interpretations in your titles are correct. If the average of the lines centers on the zero line, that means that the genes are unchanged. Above the line, activated; below the line, repressed.
- I like how you have already worked on making titles for your slides that are messages. Make sure that you read them aloud to "hear" whether they are as clear as they could be. In some cases, you are mixing up terminology (strain vs. gene). As you revise, ask yourself is this the most important point I can make about this slide?
- 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?
— Kam D. Dahlquist 16:25, 1 May 2015 (EDT)
Week 13 Feedback
- Thank you for submitting your work on time.
- Your spreadsheet is complete and correct.
- Your electronic notebook is good, but could be improved by the following:
- Say what the name of your edited file is, as well as providing the link.
- Link to your own individual assignment pages throughout the protocol when it refers to data coming from previous assignments.
- You needed to specify the changes you made to the "optimization_parameters" sheet.
— Kam D. Dahlquist 18:36, 21 April 2015 (EDT)
Week 7 Feedback
- Your Week 7 individual journal assignment was late by 27 minutes and your shared journal reflection was on time.
- Please talk to me about how you are doing your hyperlinks for the assignment. The links to your journal pages should not be on a subpage, but on your user page itself.
- Your electronic notebook was very 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 Karina worked together, not 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. You should have shown the plots that resulted and your interpretation of what they mean.
- Your handwritten notes on the analysis of the steady-state were good.
— Kam D. Dahlquist 12:45, 17 March 2015 (EDT)
Week 1 Redux
- I have reviewed your Week 1 assignment a second time; thank you for submitting your changes on time.
- I noted that your usage of the summary field has improved slightly; you have written comments in the summary field for 74% of the last 50 contributions you made. Remember, we are aiming for 100%.
- I think you have a misunderstanding about how we want you to submit assignments for this class. We want you to create a new wiki page for each week's individual assignment instead of keeping one long electronic notebook page for this class. Note that this is different than what we are doing for our research. For example, you would create the page [[Natalie Willliams Week 5]] to hold your electronic notebook and submission for the Week 5 assignment.
- Then, you will invoke your templae {{Template:Natalie Williams}} on each of those pages.
- On your template, you would have a list of links to each of the week's assignments, to each of your individual journal pages, and to each of the class journal pages. Currently, your template only has links to the Week 1 assignment and your long narrative journal page and not to the class journal assignments. You might want to take a look at what some of your classmates have done to see examples of what I mean. Please talk to me if you need further clarification.
— Kam D. Dahlquist 19:38, 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 50% of the time, but you should aim for 100%.
- Since you are using OpenWetWare e-mail link, you probably don't want to show your real e-mail address. If you do want to show it, please go ahead and make it a "maillto" link.
- Your section entitled "LMU Course BIOL398-04" is a little oddly placed. It seems like this section should be entitled "Upper Division Coursework" and then list the BIOL 398-04 with a link to the course home page. I don't think a link to your electronic notebook should be in this section, but should appear under research where you have it.
- You created a template, but did not actually invoke it on your user page. To do this, use the code {{Natalie Williams}}. I think for this reason, you did not actually have the category or links to the assignment and shared journal pages appear on your user page.
- You should remove the publication stuff that OpenWetWare automatically put on your User page as it does not apply to you. You can also remove the OpenWetWare automated text from the bottom of this talk page.
— Kam D. Dahlquist 20:51, 29 January 2015 (EST)
I've answered your question on my User talk page. — Kam D. Dahlquist 21:30, 29 January 2015 (EST)
Answer from Dr. Fitzpatrick
You asked I would like to know what your favorite book is and why?
Wow, that is a very hard one... it's like having about 1000 children and being asked which is my favorite. I love to read all sorts of things: scifi, thrillers, history, biographies, current events, economics, and of course science and math. Neal Stephenson is my favorite scifi writer, and the whole Baroque Cycle (9 books total) is great. Thriller/horror stuff, I'd have to say Peter Straub's Koko. The most recent thing I've read is Piketty's Capital in the 21st Century, which is a great econ book. The book I use the most, and reach for the most often, is Graybill's Theory and Application of Linear Model, a statistics text I used in my first year of grad school. That one is probably my favorite. I have three copies: one at home, one at LMU, and one in my consulting office. My original copy has completely decoupled in sections from the binding and cover.
Ben G. Fitzpatrick 01:29, 21 January 2015 (EST)
Hello, Natalie Williams! This is a welcome message from OpenWetWare. By the way, we've announced you on the home page! You can leave messages to any OWW member by editing their User_talk pages like this one. And don't forget to personalize your User Page so that we can get to know you better! We've included some tips below to get you started.
Spring 2015 Biomath talk
You asked I would like to know what your favorite book is and why?
Wow, that is a very hard one... it's like having about 1000 children and being asked which is my favorite. I love to read all sorts of things: scifi, thrillers, history, biographies, current events, economics, and of course science and math. Neal Stephenson is my favorite scifi writer, and the whole Baroque Cycle (9 books total) is great. Thriller/horror stuff, I'd have to say Peter Straub's Koko. The most recent thing I've read is Piketty's Capital in the 21st Century, which is a great econ book. The book I use the most, and reach for the most often, is Graybill's Theory and Application of Linear Model, a statistics text I used in my first year of grad school. That one is probably my favorite. I have three copies: one at home, one at LMU, and one in my consulting office. My original copy has completely decoupled in sections from the binding and cover.
Ben G. Fitzpatrick 01:29, 21 January 2015 (EST)
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