• 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