Natalie Williams Week 14
Running the GRNmodel on MATLAB
April 22, 2015
I ran a version of the model before coming to class. To view the outputs and figures, download the following link:
Scer vs. Spar
April 23, 2015
In class:
This file output was incorrect due to the optimization parameters. iestimate was set to 0, when it should have been equal to 1. The alpha input was also set to 1.00E-10 when it should have been equal to 0.01.
These changes were made and were rerun during class.
These are the following figures from MATLAB estimation outputs.
Out of Class
To visualize the first run where the parameters and production rates were optimized and "guessed", the out_network_weights sheet had to be deleted from the workbook. I then renamed the out_network_optimized_weights to network_optimized_weights. When that was uploaded to GRNSight, the colors as well as the thickness of the lines were seen.
Analyzing the Results of the GRNmodel
Graphs
Examine the graphs that were output by each of the runs. 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?
Fixed_b
- STB5: seems to fit the data well; the wt and spar data points are dispersed evenly along the curve
- YOX1: the model fits the data points pretty well
- CYC8: these data points are distributed evenly on the curve of the model and do not stray far from the model's curve - no strong outliers
- YLR278C: seems to fit the curve well; the wt and spar are dispersed randomly for the time points
- SWI3: data points are close to the curve
- MGA2: looks even on the curve
- ZAP1: looks good
- CIN5: looks good; see that wt sits above the models' curve while spar sits below the curve
I believe these fit the model the best due to number of inputs going into these selected number. In analyzing the normalized weight values, the arrows or bunts are thing or have moderate control (with other transcription factors involved) of the target gene. Due to the moderation, the optimized values could fit the data points better and in the middle of their respective time points.
Between Strains
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?
Fixed_b
- STB5: down regulated initially and remained down regulated; expression level was -1
- YHP1: seems initially down regulated before it becomes slightly up-regulated
- MIG2: seems to accommodate for the two high wt data points at 30 minutes
- MCM1: up-regulated continuously until its expression was equal to 1
- ZAP1: up-regulated as well; saw expression levels almost equal to 1
- MSN4: up-regulated quickly initially before plateauing
- CIN5: up-regulated; almost looks sinusoidal
Frequencies, Weights, and Production Rates
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?
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