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A General Model for Gene Regulatory Networks with Stochastic Dynamics

Authors: Andre S. Ribeiro, Rui Zhu, S. A. Kauffman

Ref.: WSEAS International Conference on Mathematical Biology and Ecology (MABE ‘06) (2006)

Abstract: We build a stochastic genetic toggle switch model using the Gillespie algorithm with time delays, as an example of a simple stochastic gene regulatory network. From this, we propose a practical modeling strategy for more complex gene regulatory networks with stochastic dynamics using the Gillespie algorithm. Here, genes interactions structure and transfer functions are made using a similar method as the one used to generate random Boolean networks, yet, its dynamics is stochastic due to being driven by the Gillespie algorithm. This model is expected to mimic realistic genes expression and regulation activities. We build random networks, in which, to each gene, an activator and repressor are randomly chosen from the set of gene expression products. Unlike previous applications of the Gillespie algorithm to simulate specific genetic networks, this modeling strategy is proposed for an ensemble approach to study the dynamical properties of these networks.