Random Effects Model for Multiple Pathway Analysis with Applications to Type II Diabetes Microarray Data.

ABSTRACT: Close to three percent of the world's population suffer from diabetes. Despite the range of treatment options available for diabetes patients, not all patients benefit from them. Investigating how different pathways correlate with phenotype of interest may help unravel novel drug targets and discover a possible cure. Many pathway-based methods have been developed to incorporate biological knowledge into the study of microarray data. Most of these methods can only analyze individual pathways but cannot deal with two or more pathways in a model based framework. This represents a serious limitation because, like genes, individual pathways do not work in isolation, and joint modeling may enable researchers to uncover patterns not seen in individual pathway-based analysis. In this paper, we pro

SUBMITTER: Pang H 

PROVIDER: S-EPMC4666561 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature