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The simulation settings are the same as in Simulation II except that we simulate the expression values of DE genes for cases from t and Gamma distributions, instead of normal distributions.
The chemical reactions and coefficient factors used to simulate the expression and signaling of TGF-β1 in the COPASI model were largely based on a recently published study by Vilar et al [20].
However, an increase of negative feedback strength of Per1 transcription led to a decrease of PER1 protein expression, and our model did not simulate the expression pattern of nuclear PER1/2 that meets the requirement.
We simulate the expression data with 200 samples in each group and repeat the entire procedure 10 times.
Each pattern P j t) was used to simulate the expression profiles of 20 DE genes, for a total of 120 DE genes.
Exploring the contribution of each of these parameters in regulating target gene expression revealed that multiple parameter combinations could simulate the expression patterns observed in vivo.
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For each network topology, two types of simulated expression data were used: Toy data : we simulated the expression data using the on/off model based on Equation (1).
We simulated the expression levels of 1,000 genes: 50 cancer genes and 950 noncancer genes.
Analogously, we simulated the expression values for the second sub-module.
Toy data: we simulated the expression data using the on/off model based on Equation (1).
Finally, TNFα simulated the expression of known NF-κB-dependent proinflammatory genes, such as IL6 and NFKB1 in a manner that was substantially reduced by BAY11-7082.
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