DISTILLER (Data Integration System To Identify Links in Expression Regulation) is a data integration framework that searches for transcriptional modules by combining expression data with information on the direct interaction between a regulator and its corresponding target genes. The framework builds upon advanced itemset mining approaches that have been designed to have good scalability, efficient memory use, and a small number of user parameters. It includes a condition selection or bicluster strategy in which co-expression of genes is required in only a significant subset of the complete condition set. By including this condition selection we can apply the algorithm to large expression compendia where interesting genes are not necessarily co-expressed in all measured conditions. Our approach also makes it straightforward to include any number of data sources related to transcriptional interactions such as additional microarrays, ChIP-chip or motif data.
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Lemmens K, De Bie T, Dhollander T, De Keersmaecker SC, Thijs IM, Schoofs G, De Weerdt A, De Moor B, Vanderleyden J, Collado-Vides J, Engelen K, Marchal K.
“DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli“.
Genome Biology , 10:R27 doi:10.1186/gb-2009-10-3-r27 (2009).