Nonlinear Coupling for Improved Stochastic Network Model: A Study of Schnakenberg Model

摘要：

Langevin equation is widely used to study the stochastic effects in molecular networks, as it often approximates well the underlying chemical master equation. However, frequently it is not clear when such an approximation is applicable and when it breaks down. Here we study the simple Schnakenberg model consisting of two molecular species whose concentrations vary and three reversible reactions. To reduce residual errors from the conventional formulation of the Langevin equation, we propose to explicitly model the effective coupling between macroscopic concentrations of different molecular species. Our preliminary results show that this formulation is effective in correcting residual errors from the original uncoupled Langevin equation and can approximate the underlying chemical master equation very accurately.

关键词： Schnakenberg model Langevin Equation Master Equation Noise

作者: Youfang Cao Jie Liang

作者单位: Shanghai Center for Systems Biomedicine,Shanghai Jiao Tong University,Shanghai 200240,China Department of Bioengineering,University of Illinois at Chicago,Chicago 60607,USA

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 379-386

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）