Dynamic association rules for gene expression data analysis.

ABSTRACT:

Background

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market bas

SUBMITTER: Chen SC 

PROVIDER: S-EPMC4606551 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature