A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

ABSTRACT: Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and

SUBMITTER: Chang TH 

PROVIDER: S-EPMC3919110 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature