DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli
Karen Lemmens1, Tijl De Bie, Thomas Dhollander
1Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium. karen.lemmens@esat.kuleuven.be
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.
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