Title :
Modeling genetic network by hybrid GP
Author :
Ando, Shin ; Sakamoto, Erina ; Iba, Hitoshi
Author_Institution :
Grad. Sch. of Eng., Tokyo Univ., Japan
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;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1006249
