Inferring transcriptional modules from ChIP-chip, motif and microarray data

doi:10.1186/gb-2006-7-5-r37

Genome Biology

Volume 7
Issue 5

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Lemmens K
Dhollander T
De Bie T
Monsieurs P
Engelen K
Smets B
Winderickx J
De Moor B
Marchal K

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Dhollander T
De Bie T
Monsieurs P
Engelen K
Smets B
Winderickx J
De Moor B
Marchal K
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Inferring transcriptional modules from ChIP-chip, motif and microarray data

Karen Lemmens¹ , Thomas Dhollander¹ , Tijl De Bie² , Pieter Monsieurs¹ , Kristof Engelen¹ , Bart Smets³ , Joris Winderickx³ , Bart De Moor¹ and Kathleen Marchal¹^,4

¹BIOI@SCD, Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg, B-3001 Heverlee, Belgium

²Research Group on Quantitative Psychology, Department of Psychology, KU Leuven, Tiensestraat, B-3000 Leuven, Belgium

³Molecular Physiology of Plants and Micro-organisms Section, Biology Department, KU Leuven, Kasteelpark Arenberg, B-3001 Heverlee, Belgium

⁴CMPG, Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg, B-3001 Heverlee, Belgium

author email corresponding author email

Genome Biology 2006, 7:R37doi:10.1186/gb-2006-7-5-r37


Published:	5 May 2006

Subject areas: Bioinformatics, Genetics, Molecular biology

Abstract

'ReMoDiscovery' is an intuitive algorithm to correlate regulatory programs with regulators and corresponding motifs to a set of co-expressed genes. It exploits in a concurrent way three independent data sources: ChIP-chip data, motif information and gene expression profiles. When compared to published module discovery algorithms, ReMoDiscovery is fast and easily tunable. We evaluated our method on yeast data, where it was shown to generate biologically meaningful findings and allowed the prediction of potential novel roles of transcriptional regulators.