Integrating human omics data to prioritize candidate genes.

ABSTRACT:

Background

The identification of genes involved in human complex diseases remains a great challenge in computational systems biology. Although methods have been developed to use disease phenotypic similarities with a protein-protein interaction network for the prioritization of candidate genes, other valuable omics data sources have been largely overlooked in these methods.

Methods

With this understanding, we proposed a method called BRIDGE to prioritize candidate genes by integrating disease phenotypic similarities with such omics data as protein-protein interactions, gene sequence similarities, gene expression patterns, gene ontology annotations, and gene pathway memberships. BRIDGE utilizes a multiple regression model with lasso penalty to automatically weight different d

SUBMITTER: Chen Y 

PROVIDER: S-EPMC3878333 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature