Ant colony optimisation of decision tree and contingency table models for the discovery of gene–gene interactions


During this study, ant colony optimisation (ACO) algorithm is employed to derive near-optimal interactions between a variety of single nucleotide polymorphisms (SNPs). This approach is employed to discover small numbers of SNPs that are combined into a call tree or contingency table model. The ACO algorithm is shown to be terribly strong as it's proven to be ready to find results that are discriminatory from a statistical perspective with logical interactions, call tree and contingency table models for varied numbers of SNPs considered in the interaction. A giant number of the SNPs discovered here are already identified in massive genome-wide association studies to be related to type II diabetes in the literature, lending additional confidence to the results.

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