Ant colony optimisation of decision tree and contingency table models for the discovery of gene–gene interactions PROJECT TITLE :Ant colony optimisation of decision tree and contingency table models for the discovery of gene–gene interactionsABSTRACT: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. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest New Results on Tracking Control Based on the T–S Fuzzy Model for Sampled-Data Networked Control System Voltage security in AC microgrids: a power flow-based approach considering droop-controlled inverters