Nika Vafadari Week 14/15
Electronic Lab Notebook Week 14/15
To identify the transcription factors that play a vital role in regulating the response to cold shock in S. cerevisiae through the manipulation of gene regulatory network dynamics.
Methods and Results
Dynamical Systems Modeling of your Gene Regulatory Network
For last week's assignment, you created a Microsoft Excel input workbook for the model. Now you are ready to run the model and analyze the results. The software we will use is called GRNmap, which stands for Gene Regulatory Network Modeling and Parameter Estimation. It is written in MATLAB and can be run from code or run as a stand-alone executable if you don't have MATLAB installed. However, it can only be run in Windows, not on Macs.
- To run GRNmap from code, you must have MATLAB R2014b installed on your computer.
- Download the GRNmap v1.4.4 code from the GRNmap Downloads page.
- Unzip the file. (Right-click, 7-zip > Extract here)
- Launch MATLAB R2014b.
- Open GRNmodel.m, which will be in the directory that you unzipped GRNmap-1.4.4 > matlab
- Click the Run button (green "play" arrow).
- You will be prompted to select your input workbook.
- You will see an optimization diagnostics graphic that shows the progress of the estimation.
- When the run is over, expression plots will display.
- Output .xlsx and .mat files will be saved in the same folder as your input folder, along with .jpg files containing the optimization diagnostic and individual expression plots. Save these files.
- Note that if you need to run GRNmap again, you should not use the same directory for the input file. Currently, GRNmap will overwrite previous output.
- Also note that you should run the model on the same computer if you want to compare model runs.
Analyzing the Modeling Results
In class on April 25, we will take a look at the modeling results and discuss how to analyze them. We will discuss:
- LSE/minLSE ratio
- MSE's and expression plots for individual genes in relation to their ANOVA p values
- Visualization of the weighted graph with GRNsight
- Making bar charts to give a graphical representation of the parameter values.
Based on these analyses, you will propose a some additional in silico experiments that you can do with the model. Some ideas are:
- For our initial runs, we estimated all three parameters w, P, and b.
- How do the modeling results change if P is instead fixed and w and b are estimated?
- How do the modeling results change if b is fixed and w and P are estimated?
- How do the modeling results change if P and b are fixed, and only w is estimated?
- For our initial runs, we included all three microarray datasets, wt, Δgln3, and Δhap4.
- What happens to the results if we base the estimation on just two strains (wt + one deletion strain)?
- What happens to the results if we base the estimation on just the wt strain data?
- When viewing the modeling results in GRNsight, you may determine that one or more genes in the network does not appear to be doing much.
- What happens to the modeling results if you delete this gene from the network and re-run the model (remember you will have to delete references to this gene in all worksheets of the input file).
- SWI5 and ACE2 selected for deletion.
- changes in Optimized weight parameters (w), Optimized production rates (P), and Optimized threshold b parameters analyzed
- all corresponding files uploaded to Nika Week 14/15 folder in class folder
- results discussed and posted in final presentation
Data and Files
Through the deletion of SWI5 and ACE2 it was found that deletion of SWI5 resulted in no changes while deletion of ACE2 resulted in drastic changes in the optimized weight parameters specifically in relation to connections including SWI5, YOX1 and MCM1. Through analysis of these changes YOX1, MCM1 and ACE2 were identified as playing a vital role in the regulation of the response to cold shock in S. cerevisiae.
- Except for what is noted above, this individual journal entry was completed by me and not copied from another source.
- Nika Vafadari 06:06, 3 May 2017 (EDT):
- Dahlquist, Kam D. (2017) BIOL398-05/S17:Week 14/15. Retrieved from http://www.openwetware.org/wiki/BIOL398-05/S17:Week_14/15 on 3 May 2017.
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