| Literature DB >> 22025762 |
Michael Mooney1, Beth Wilmot, The Bipolar Genome Study, Shannon McWeeney.
Abstract
Enormous data collection efforts and improvements in technology have made large genome-wide association studies a promising approach for better understanding the genetics of common diseases. Still, the knowledge gained from these studies may be extended even further by testing the hypothesis that genetic susceptibility is due to the combined effect of multiple variants or interactions between variants. Here we explore and evaluate the use of a genetic algorithm to discover groups of SNPs (of size 2, 3, or 4) that are jointly associated with bipolar disorder. The algorithm is guided by the structure of a gene interaction network, and is able to find groups of SNPs that are strongly associated with the disease, while performing far fewer statistical tests than other methods.Entities:
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Year: 2011 PMID: 22025762 PMCID: PMC3748153 DOI: 10.1109/TCBB.2011.145
Source DB: PubMed Journal: IEEE/ACM Trans Comput Biol Bioinform ISSN: 1545-5963 Impact factor: 3.710