Bayesian approach to transforming public gene expression repositories into disease diagnosis databases.

ABSTRACT: The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and

SUBMITTER: Huang H 

PROVIDER: S-EPMC2872390 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature