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Dynamic Fuzzy Clustering for Analyzing Microarray GeneExpression Data Based on a Parallel Immune Genetic Algorithm

ZHENG Ming, LIU Guixia, ZHOU Chunguang, WANG Han, ZHENG Xiao hong, LI Yan wen   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2008-07-22 Revised:1900-01-01 Online:2009-01-26 Published:2009-01-26
  • Contact: LIU Guixia

Abstract: We proposed an improved parallel immune genetic algorithm. The introduced island concept on the population size can make the sizes of populations variable; The immune operator introduced in the fitness functioncan avoid the algorithm premature convergence. Hence, this method can prevent local convergence in the optimal algorithm in a great extent, and make the probability of approaching the global convergence bigger. The algorithm was used via the Yeast Saccharomyces cerevisiae cell cycle gene expression profile from SGD to coexpress clusters. Compared to the experiment analyzed by Spellman for functional genomics, the efficiencyof this algorithm in the functional genomics can be proved.

Key words: dynamic fuzzy clustering, parallel immune genetic algo rithm, immune operator, island

CLC Number: 

  • TP18