DocumentCode :
419076
Title :
Real-coded GA with multimodal uniform distribution
Author :
Ando, Shin ; Iba, Hitoshi
Author_Institution :
Dept. of Electron., Tokyo Univ., Japan
Volume :
1
fYear :
2004
fDate :
19-23 June 2004
Firstpage :
827
Abstract :
This paper proposes a method to capture the dynamics of gene expression data using S-system formalism and construct genetic network models. The proposed method exploits the probabilistic heuristic search and divide-and-conquer approach to generate candidate network structures. In evaluating the network structure, we attempt a primitive integration of other knowledge to the statistical criterion. The robustness analysis uses Z-score to identify significant parameters from results of stochastic search. We evaluated the proposed method on artificial generated data and E.coli mRNA expression data.
Keywords :
divide and conquer methods; genetic algorithms; statistical analysis; stochastic processes; S-system formalism; divide-and-conquer approach; gene expression data; genetic algorithm; genetic network; mRNA expression data; multimodal distribution; probabilistic heuristic search; real-coded GA; robustness analysis; stochastic search; uniform distribution; Bioinformatics; Biological system modeling; Data engineering; Gene expression; Genetic engineering; Informatics; Noise level; Parameter estimation; Robustness; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
Type :
conf
DOI :
10.1109/CEC.2004.1330946
Filename :
1330946
Link To Document :
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