A Hybrid Petri Net Model of the Eukaryotic Cell Cycle

System level understanding of the repetitive cycle of cell growth and division is crucial for disclosing many unexpected principles of biological organisms. The deterministic or stochastic approach are alone not sufficient to study such cell regulation due to the complex reaction network and the existence of reactions with different time scales. Thus, integration of both approaches is necessary to study such biochemical networks. In this paper we present a hybrid Petri net model to study the eukaryotic cell cycle using Generalised Hybrid Petri Nets. The proposed model is intuitively and graphically represented through Petri net primitives. Moreover, it can capture intrinsic and extrinsic noises and deploys stochastic as well as deterministic reactions. Additionally, selfmodifying weights are motivated and introduced to Snoopy – a tool for animating and simulating Petri nets.