Gene Specific Co-regulation Discovery: An Improved Approach

Authors:
Ji Zhang;Qing Liu;Kai Xu
Affiliations:
CSIRO Tasmanian ICT Centre, Hobart, Australia 7001;CSIRO Tasmanian ICT Centre, Hobart, Australia 7001;CSIRO Tasmanian ICT Centre, Hobart, Australia 7001
Venue:
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Year:
2009

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Abstract

Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a particular gene of interest, called the target gene , identify its strongly co-regulated genes and the condition subsets where such strong gene co-regulations are observed. The study on this problem can contribute to a better understanding and characterization of the target gene. The existing method, using the genetic algorithm (GA), is slow due to its expensive fitness evaluation and long individual representation. In this paper, we propose an improved method for finding gene specific co-regulations. Compared with the current method, our method features a notably improved efficiency. We employ k NN Search Table to substantially speed up fitness evaluation in the GA. We also propose a more compact representation scheme for encoding individuals in the GA, which contributes to faster crossover and mutation operations. Experimental results with a real-life gene microarray data set demonstrate the improved efficiency of our technique compared with the current method.