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.

Exploiting stochastic Petri nets with fuzzy parameters to predict efficient drug combinations for Spinal Muscular Atrophy

“…Lamprecht et al [13] used SPNs to create model of Ca 2+ release sites composed of a number of intracellular channels that have stochastic behavior, and Marwan et al [14] investigated enteric bacteria phosphate regulation by using SPNs, while Castaldi et al [15] developed SPN model of the tissue factor-induced coagulation cascade. Liu et al [16] used fuzzy SPNs to create a yeast polarization model, and Bashirov et al [17] presented stochastic simulation-based validation and analysis of the p16-mediated pathway, the disruption of which is among major causes of human cancers. Software tools used to conduct the above research include Snoopy [18], Möbius [19] and GreatSPN [20], while https://www.informatik.unihamburg.de/cgi-bin/TGI/tools/ collects links to 23 Petri net tools and software supporting SPNs.…”

“…To run the application, we simply set the initial data, that is, choose composition of the drug candidates by placing tokens in corresponding places. [17,33]. The reaction rates are calibrated in terms of stochastic replications by further averaging obtained results.…”