Inferring a system of differential equations for a gene regulatory network by using genetic programming

Author

Sakamoto, Erina ; Iba, Hitoshi

Author_Institution

Dept. of Inf. Commun. Eng., Tokyo Univ., Japan

Volume

1

fYear

2001

fDate

2001

Firstpage

720

Abstract

Describes an evolutionary method for identifying a gene regulatory network from the observed time series data of the gene´s expression. We use a system of ordinary differential equations as a model of the network and infer their right-hand sides by using genetic programming (GP). To explore the search space more effectively in the course of evolution, the least mean squares (LMS) method is used along with ordinary GP. We apply our method to three target networks and empirically show how successfully GP infers the systems of differential equations

Keywords

biocontrol; biology computing; differential equations; genetic algorithms; genetics; least mean squares methods; mathematics computing; time series; equation right-hand sides; evolutionary method; gene expression; gene regulatory network identification; genetic programming; inference; least mean squares method; ordinary differential equation system; search space exploration; time series data; Bioinformatics; DNA; Differential equations; Genetic engineering; Genetic expression; Genetic programming; Least squares approximation; Power system modeling; Space exploration; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2001. Proceedings of the 2001 Congress on

Conference_Location

Seoul

Print_ISBN

0-7803-6657-3

Type

conf

DOI

10.1109/CEC.2001.934462

Filename

934462