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