Hybrid modeling and simulation of stochastic effects on progression through the eukaryotic cell cycle

• DOI: 10.1063/1.3677190
• Publication Date: 2012-01-17T23:59:15Z
• Authors: Zhen Liu; Yang Pu; Fei Li; Clifford A. Shaffer; Stefan Hoops; John J. Tyson; Yang Cao
• Keywords: Stochastic simulation; Stochastic modelling; Deterministic simulation

The eukaryotic cell cycle is regulated by a complicated chemical reaction network. Although many deterministic models have been proposed, stochastic are desired to capture noise in the resulting from low numbers of critical species. However, converting model into one that accurately captures effects can result complex hard build and expensive simulate. In this paper, we first apply hybrid (mixed stochastic) simulation method such model. With proper partitioning reactions between methods, generates same primary characteristics level as Gillespie's algorithm, but with better efficiency. By studying results generated various partitionings reactions, developed new strategy for modeling cycle. approach not limited using mass-action rate laws. Numerical experiments demonstrate our consistent noisy progression, yields statistics accord experimental observations.