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ABSTRACT: Background
A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions.Results
Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-
SUBMITTER: Chou JW
PROVIDER: S-EPMC2194742 | biostudies-literature | 2007 Nov
REPOSITORIES: biostudies-literature