Open Access Method

DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli

Karen Lemmens1, Tijl De Bie23, Thomas Dhollander1, Sigrid C De Keersmaecker4, Inge M Thijs4, Geert Schoofs4, Ami De Weerdt4, Bart De Moor1, Jos Vanderleyden4, Julio Collado-Vides5, Kristof Engelen4 and Kathleen Marchal4*

Author Affiliations

1 Department of Electrical engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium

2 Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, UK

3 OKP Research Group, Katholieke Universiteit Leuven, Leuven 3000, Belgium

4 Department of Microbial and Molecular systems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium

5 Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca AP 565-A, México

For all author emails, please log on.

Genome Biology 2009, 10:R27 doi:10.1186/gb-2009-10-3-r27

Published: 6 March 2009

Abstract

We present DISTILLER, a data integration framework for the inference of transcriptional module networks. Experimental validation of predicted targets for the well-studied fumarate nitrate reductase regulator showed the effectiveness of our approach in Escherichia coli. In addition, the condition dependency and modularity of the inferred transcriptional network was studied. Surprisingly, the level of regulatory complexity seemed lower than that which would be expected from RegulonDB, indicating that complex regulatory programs tend to decrease the degree of modularity.