Modeling of genetic regulation networks based on Immune Memory Particle Swarm Optimization

摘要：

A reverse-problem in modern systems biology focuses on modeling and simulation of gene regulatory networks, metabolic networks from time-course data. With the depth of research, not only the network structures but also its dynamics are paid more attention. We proposed a method to model the gene regulatory networks in Escherichia coli by using Immune Memory Particle Swarm Optimization(IM-PSO) and Ordinary differential equations (ODEs). This method successfully inferred the dynamics of a small regulation networks for 7 genes using only 4 time-course data of gene expression.

关键词： gene regulatory netoworks ordinary differential equations Immune Memory Particle Swarm Optimization

作者: Xi Chen Nini Rao Shanglei Xu Yunhe Wang Yuan Zhou

作者单位: School of Life Science & Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R.China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1773-1776

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）