Double-bottom chaotic map particle swarm optimization based on chi-square test to determine gene-gene interactions.

ABSTRACT: Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease

SUBMITTER: Yang CH 

PROVIDER: S-EPMC4033510 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature