Discover Gene Specific Local Co-regulations Using Progressive Genetic Algorithm

  • Authors:
  • Ji Zhang;Qigang Gao;Hai Wang

  • Affiliations:
  • Dalhousie University, Canada;Dalhousie University, Canada;Saint Mary's University, Canada

  • Venue:
  • ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
  • Year:
  • 2006

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Abstract

The problem of gene specific co-regulation discovery is that, for a particular gene of interest, identify its closely coregulated genes and the associated subsets of experimental conditions in which such co-regulations occur. The coregulations are local in the sense that they occur in some subsets of full experimental conditions. In this paper, we propose an innovative method for finding gene specific coregulations using genetic algorithm (GA). Two novel ad hoc GAs, the single-stage and two-stage progressive GA, are proposed. They are called progressive because the initial population for the GA in a window position inherits the top-ranked individuals obtained in the preceding window position, enabling them to achieve better accuracy than the non-progressive algorithm. Experimental results with reallife gene expression data demonstrate the efficiency and effectiveness of our technique in discovering gene specific coregulations.