Relating gene expression data on two-component systems to functional annotations in Escherichia coli

Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step. Results: We have developed an algorithm that relates patterns of gene expression in a set of microarray experiments to functional groups in one step. Our only assumption is that patterns cooccur frequently. The effectiveness of the algorithm is demonstrated as part of a study of regulation by two-component systems in Escherichia coli. The significance of the relationships between expression data and functional annotations is evaluated based on density histograms that are constructed using product similarity am...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Anne M. Denton, Jianfei Wu, Megan K. Townsend, Preeti Sule, Birgit M. Prüß
• Keywords: Algorithm, BMCBI 2008, Gene Expression, Step