Evolving additive tree model for inferring gene regulatory networks

Abstract

Gene regulatory networks have been studied in the past few years and it is still a hot topic. This paper presents a different evolutionary method for inferring gene regulatory networks (GRNs) using a system of ordinary differential equations (ODEs) as a network model based on time-series microarray data. An evolutionary algorithm based on the additive tree-structure model is applied to identify the structure of the model and genetic algorithm (GA) is used to optimize the parameters of the ODEs. The experimental results show that the proposed method is feasible and effective for inferring gene regulatory networks. © 2014 Springer International Publishing Switzerland.