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MOACO Biclustering of gene expression data

  • Junwan Liu*
  • , Zhoujun Li
  • , Xiaohua Hu
  • , Yiming Chen
  • *此作品的通讯作者
  • Central South University of Forestry & Technology
  • Drexel University
  • National University of Defense Technology

科研成果: 期刊稿件文章同行评审

摘要

Many bioinformatics data sets come from DNA microarray experiments. Biclustering of gene expression data can identify genes with similar behaviour with respect to different conditions. Ant Colony Optimisation (ACO) algorithms have been shown to be effective problem solving strategies for a wide range of problem domains. Multiple Objective Ant Colony Optimisation (MOACO) mainly focuses on solving the multiple objective combinatorial optimisation problems. This paper incorporates crowding update technology into MOACOB and proposes crowding MOACO biclustering algorithm to mine biclusters from gene expression data. Experimental results are shown for biclustering algorithm on two real gene expression data.

源语言英语
页(从-至)58-72
页数15
期刊International Journal of Functional Informatics and Personalised Medicine
3
1
DOI
出版状态已出版 - 2010

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