Stochastic Simulation-based Prediction of the Behavior of the p16-mediated Signaling Pathway

Abstract

In this work we use hybrid Petri nets to create a model of the p16-mediated signaling pathway in higher eukaryotes and conduct its stochastic simulation-based validation by wet lab observations available from literature. The validation is conducted in terms of stochastic simulations with respect to the wild-type p16 protein and its mutated form. Our model catches the behavior of the major molecular regulators of the p16-mediated signaling pathway in wild-type cells as well as when DNA damage is detected or replicative senescence occurs. We observe that the stochastic model predicts some characteristics of the underlying pathway more clearly, evidently and perspicuously compared to the deterministic model, enriching the breadth and the quality of the outcome.