Parameter Optimization in Network Dynamics Including Unmeasured Variables by the Symbolic-numeric Approach

摘要：

In this report, we propose a new symbolic-numeric method of differential algebra and a numerical parameter optimization algorithm. First, we utilize differential elimination, which is an algebraic approach for rewriting a system of differential equations into another equivalent system, to derive the constraints between the kinetic parameters from the original system. Second, we introduce these constraints to effectively optimize the parameters into a genetic algorithm, Real-Coded Genetic Algorithms (RCGAs), which is a numerical parameter optimizing method. To evaluate the ability of our method, we performed a simulation study for an artificial biological network including one measured and three unmeasured molecules. As a result, our method, the symbolic-numeric method of differential elimination and RCGAs, precisely estimated the kinetic parameters in the simulated network, while RCGAs failed. Thus, our method is useful for analyzing the dynamics of a biological network including unmeasured molecules.

关键词： symbolic-numeric method differential elimination real-coded genetic algorithms (RC-GAs)

作者: Masahiko Nakatsui Katsuhisa Horimoto

作者单位: Computational Biology Research Center,National Institute of Advanced Industrial Science and Technolo Computational Biology Research Center,National Institute of Advanced Industrial Science and Technolo

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: 245-253

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）