Abstract
A discrete time model of large gene expression regulatory networks is considered. Transcriptional degrees of regulations and activation thresholds are shuffled randomly that helps to study the highly reproducible dynamical patterns of regulatory processes in a lack of empirical data concerning genetic switches. The multistationarity and multiperiodicity of oscillations exhibited by the system relay upon the feedback circuits. Statistics of their appearance depends upon the relative number of negative regulations between the genes of network, the number of cycles in the maximal graph, and their lengths. The model defined on the scalable graphs demonstrates the high persistence in oscillations and the high error tolerance.
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