Inferring biological functions and associated transcriptional regulators using gene set expression coherence analysis

Background: Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene sets can provide clues on which functional themes or regulatory sequence motifs are associated with individual gene clusters. In spite of the potential utility, gene clustering and enrichment analysis have been used in separate platforms, thus, the development of integrative algorithm linking both methods is highly challenging. Results: In this study, we propose an algorithm for discovery of molecular functions and elucidation of transcriptional logics using two kinds of gene information, functional and regulatory motif gene sets. The algorithm, termed gene set expression coherence analysis first selects functional gene sets with significantly high expression coherences. Those candidate gene sets are further processed into a number of functionally related themes or functional clusters according to the expressi...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Tae-Min Kim, Yeun-Jun Chung, Mun-Gan Rhyu, Myeong Ho Jung
• Keywords: BMCBI 2007, Gene, Gene Sets, Motif Gene Sets