Hybrid Petri nets for modelling the eukaryotic cell cycle

Abstract

System level understanding of the repetitive cycle of cell growth and division is crucial for disclosing many unknown principles of biological organisms. The deterministic or stochastic approach - when deployed separately - are not sufficient to study such cell regulation due to the complexity of the reaction network and the existence of reactions at different time scales. Thus, an integration of both approaches is advisable to study such biochemical networks. In this paper we show how Generalised Hybrid Petri Nets can be used to intuitively represent and simulate the eukaryotic cell cycle. Our model captures intrinsic as well as extrinsic noise and deploys stochastic as well as deterministic reactions. Additionally, marking-dependent arc weights are biologically motivated and introduced to Snoopy - a tool for animating and simulating Petri nets in various paradigms. © 2013 Springer-Verlag.