Modeling genetic network by hybrid GP

Author

Ando, Shin ; Sakamoto, Erina ; Iba, Hitoshi

Author_Institution

Grad. Sch. of Eng., Tokyo Univ., Japan

Volume

1

fYear

2002

Firstpage

291

Lastpage

296

Abstract

We present an evolutionary modeling method for modeling genetic regulatory networks. The method features a hybrid algorithm of genetic programming with statistical analysis to derive systems of differential equations. Genetic programming and the least mean squares method were combined to identify a concise form of regulation between the variables from a given set of time series. Results of multiple runs were statistically analyzed to indicate the term with robust and significant influence. Our approach was evaluated in artificial data and real world data

Keywords

differential equations; genetic algorithms; least mean squares methods; statistical analysis; artificial data; differential equations; evolutionary modeling method; genetic regulatory network modeling; hybrid algorithm; hybrid genetic programming; least mean square method; multiple runs; real world data; regulation; statistical analysis; time series; Chemicals; Circuits; Differential equations; Gene expression; Genetic programming; Least mean squares methods; Proteins; Robustness; Statistical analysis; Switches;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7282-4

Type

conf

DOI

10.1109/CEC.2002.1006249

Filename

1006249