An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier]


In this paper, a completely unique ant colony optimization and tabu list approach for the invention of gene-gene interactions in genome-wide association study data is proposed. The tactic is tested on a variety of diseases drawn from the massive established database, the Wellcome Trust Case Control Consortium that contains hundreds of thousands of tiny DNA changes called single nucleotide polymorphisms. To research full scale genome-wide association study information, the standard ant colony optimization algorithm has been tailored, with tournament path choice, a subset based mostly approach, and tabu list included in the algorithm. These modifications, in addition to the employment of a statistical test of significance of single nucleotide polymorphism interactions as a fitness perform, greatly increase execution speeds and permit the invention of combos of single nucleotide polymorphisms that can discriminate cases and controls. The methodology is applied to several giant-scale genome-wide association study disease datasets namely, inflammatory bowel disease, rheumatoid arthritis, kind I diabetes and kind II diabetes patients to get putative gene-gene interactions in affordable time on modest hardware.

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