Identification of type 2 diabetes-associated combination of SNPs using support vector machine.

ABSTRACT:

Background

Type 2 diabetes mellitus (T2D), a metabolic disorder characterized by insulin resistance and relative insulin deficiency, is a complex disease of major public health importance. Its incidence is rapidly increasing in the developed countries. Complex diseases are caused by interactions between multiple genes and environmental factors. Most association studies aim to identify individual susceptibility single markers using a simple disease model. Recent studies are trying to estimate the effects of multiple genes and multi-locus in genome-wide association. However, estimating the effects of association is very difficult. We aim to assess the rules for classifying diseased and normal subjects by evaluating potential gene-gene interactions in the same or distinct biological p

SUBMITTER: Ban HJ 

PROVIDER: S-EPMC2875201 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature