A genetic ensemble approach for gene-gene interaction identification

Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods: In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA) and an ensemble of classifiers (called genetic ensemble). Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP) subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gen...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bing Bing Zhou
• Keywords: BMCBI 2010, Gene-environment Interactions, Gene-gene Interaction, Genetic Ensemble Algorithm