Inference of Differential Equation Models by Multi Expression Programming for Gene Regulatory Networks

This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential equations (ODEs) as a model of network. The structure of ODE is inferred by the Multi Expression Programming (MEP) and the ODE's parameters are optimized by using particle swarm optimization (PSO). The proposed method can acquire the best structure of the ODE only by a small population, and also by partitioning the search space of system of ODEs can be reduced significantly. The effectiveness and accuracy of the proposed method are demonstrated by using synthesis data from the artificial genetic networks.

• Type: Journal
• Year: 2009
• Where: ICIC
• Authors: Bin Yang, Yuehui Chen, Qingfang Meng
• Keywords: Applied Computing, Gene Regulatory Network, ICIC 2009, Multi Expression Programming, Particle Swarm Optimization