BIOL398-04/S15:Week 13

BIOL398-04: Biomathematical Modeling

MATH 388-01: Survey of Biomathematics

Loyola Marymount University

This journal entry is due on Tuesday, April 21 at midnight PDT (Monday night/Tuesday morning). NOTE that the server records the time as Eastern Daylight Time (EDT). Therefore, midnight will register as 03:00.

Individual Journal Assignment

• Store this journal entry as "username Week 13" (i.e., this is the text to place between the square brackets when you link to this page).
• Create the following set of links. (HINT: These links should all be in your personal template that you created for the Week 1 Assignment; you should then simply invoke your template on each new journal entry.)
• Don't forget to add the "BIOL398-04/S15" category to the end of your wiki page.

For your assignment this week, you will keep an electronic laboratory notebook on your individual wiki page that records all the manipulations you perform on the data and the answers to the questions throughout the protocol. We will be working on the protocols in class on this week. Whatever you do not finish in class will be homework to be completed by the Week 13 journal deadline.

REMINDER: you should "turn on" the file extensions using the instructions found on the Help page before beginning today's work.

Corrections to Week 12 Individual Journal Assignment

Please go back and correct your Week 12 individual journal entries based on the feedback you received in class on Thursday, April 16. The corrections are due by the Week 13 deadline of midnight Tuesday, April 21 PDT. Grades will be not be assigned for the Week 12 entries until after the correction deadline. Make sure your Week 12 journal entry has the following:

• You and your partner should have the same network with the same genes.
• Only delete genes from the network that have zeroes in both the column and row for that gene.
• Give the number of edges and degree distribution charts for the small (binding and expression), medium (binding only), and large (binding plus expression) networks.
• Show the GRNsight graph for the small, medium, and large networks in your PowerPoint presentation.
• Use only your medium network for this week's protocol below. You and your partner should have identical input spreadsheets after following this procedure. You should each do the procedure independently, however, so that you can check each other's work.

Create the Input Excel Workbook for the Model

1. Your file will be similar to the file "Input_4_gene_forward_correct_params.xlsx" that you used in class on Tuesday, but with your expression data and network. You should download this file, change the name, and edit it to include your data. Make sure to give it a meaningful filename that includes your last name or initials. (The file can be found in this zipped file on LionShare.)
2. The first thing you need to do is determine the transcription factors that you are including in your network. You are going to use the "transposed" Regulation Matrix that you generated from YEASTRACT in the Week 12 Assignment.
• Copy the transposed matrix from your "network" sheet and paste it into the worksheets called "network" and "network_weights".
• Note that the transcription factor names have to be in the same order and same format across the top row and first column. CIN5 does not match Cin5p, so the latter will need to be changed to CIN5 if you have not already done so.
• It may be easier for you if you put the transcription factors in alphabetical order (using the sort feature in Excel), but whether you leave your list the same as it is from the YEASTRACT assignment or in alphabetical order, make sure it is the same order for all of the worksheets.
3. The next worksheet to edit is the one called "degradation_rates".
• Paste your list of transcription factors from your "network" sheet into the column named "StandardName". You will need to look up the "SystematicName" of your genes. YEASTRACT has a feature that will allow you to paste your list of standard names in to retrieve the systematic names here.
• Next, you will need to look up the degradation rates for your list of transcription factors. These rates have been calculated from protein half-life data from a paper by Belle et al. (2006). Look up the rates for your transcription factors from this file and include them in your "degradation_rates" worksheet.
• If a transcription factor does not appear in the file above, use the value "0.027182242" for the degradation rate.
4. The next worksheet to edit is the one called "production_rates".
• Paste the "SystematicName" and "StandardName" columns rom your "degradation_rates" sheet into the "production_rates" sheet.
• The initial guesses for the production rates we are using for the model are two times the degradation rate. Compute these values from your degradation rates and paste the values into the column titled "ProductionRate".
5. Next you will input the expression data for the wild type strain and the other strain your partner is using (dcin5, dgln3, dhmo1, dzap1, spar). You need to include only the data for the genes in your network, in the same order as they appear in the other worksheets.
• Put the wild type data in the sheet called "wt".
• The sample spreadsheet has a worksheet named "dcin5". Change this name to match the strain you are using (listed above). The instructions below should be followed for each strain sheet.
• Paste the SystematicName and StandardName columns from one of your previous sheets into this one.
• This data in this sheet is the Log Fold Changes for each replicate and each timepoint from your Week 11 Assignment. We are only going to use the cold shock timepoints for the modeling. Thus your column headings for the data should be "15", "30", and "60". There will be multiple columns for each timepoint (typically 4) to represent the replicate data, but they will all have the same name. For example, you may have four columns with the header "15".
• Copy and paste the data from your Week 11 spreadsheet into this one. You need to include only the data for the genes in your network. Make sure that the genes are in the same order as in the other sheets.
6. We will only be editing parts of the "optimization_parameters" worksheet.
• For the parameter "time" (Cell A13), replace what is in the sample file with "15", "30", and "60", since these are the timepoints we have in our data.
• For the parameter "Strain" (Cell A14), replace "dcin5" with the name of the second strain you are using, making sure that the capitalizaiton and spelling is the same as what you named the worksheet containing that strain's expression data.
7. For the parameter "Deletion", leave the zero in cell B15. In cell C15, put a number corresponding to the position in the list of gene names that the gene that was deleted appears. In the sample file, CIN5 is number 3 in the list of 4 genes.
• For the parameter "simtime", you perform the forward simulation of the expression in five minute increments from 0 to 60 minutes. Thus, this row should read: "simtime", "0", "5", "10", ..., "60".
8. The last sheet you will need to modify is called "network_b".
• Paste in the list of standard names for your transcription factors from one of your previous sheets. Note that this sheet does not have a column for the systematic name.
• Cell A1 in the sample files has the text "rows genes affected/cols genes controlling". I believe you can either have this text in cell A1 or "StandardName".
• The "threshold" value for each gene should be "0".
9. When you have completed the modifications to your file, upload it to LionShare and send Dr. Dahlquist and Dr. Fitzpatrick and e-mail with a link to the file. Your assignment will not be considered complete until we have successfully downloaded the correct file from you. If you need assistance with LionShare, please ask well ahead of the assignment deadline.

Appendix: Full explanation of the "optimization_parameters" sheet

• alpha: Penalty term weighting (from an L-curve analysis)
• kk_max: Number of times to re-run the optimization loop: in some cases re-starting the optimization loop can improve performance of the estimation.
• MaxIter: Number of times MATLAB iterates through the optimization scheme. If this is set too low, MATLAB will stop before the parameters are optimized.
• TolFun: How different two least squares evaluations should be before it says it's not making any improvement
• MaxFunEval: maximum number of times it will evaluate the least squares cost
• TolX: How close successive least squares cost evaluations should be before MATLAB determines that it is not making any improvement.
• Sigmoid: =1 if sigmoidal model, =0 if Michaelis-Menten model
• iestimate: =1 if want to estimate parameters and =0 if the user wants to do just one forward run
• iGraphs: =1 to output graphs; =0 to not output graphs
• fix_P: =1 if the user does not want to estimate the production rate, P, parameter, use initial guess and never change; =0 to estimate
• fix_b: =1 if the user does not want to estimate the b parameter, use initial guess and never change; =0 to estimate
• time: A row containing a list of the time points when the data was collected experimentally. Should correspond to the timepoint column headers in the expression sheets.
• Strain: A row containing a list of all of the strains for which there is expression data in the workbook. Should correspond to the names of the sheets for each strain.
• Sheet: A row where each entry is the order number of the sheet (left to right) that corresponds to the list of strains above.
• Deletion: Gives the index of the gene in the network sheet that has been deleted in each strain listed above. For example, if data has been provided for the CIN5 deletion strain, then give the index number from the network sheet corresponding to CIN5.
• simtime: A list of times for which the forward simulation should be evaluated.

Shared Journal Assignment

I forgot to post the shared journal assignment. Therefore, there will not be a shared journal assignment for this week.

Kam D. Dahlquist 11:52, 20 April 2015 (EDT)