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

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 dep...

Descripción completa

Detalles Bibliográficos
Autores principales: Lemmens, Karen, De Bie, Tijl, Dhollander, Thomas, De Keersmaecker, Sigrid C, Thijs, Inge M, Schoofs, Geert, De Weerdt, Ami, De Moor, Bart, Vanderleyden, Jos, Collado-Vides, Julio, Engelen, Kristof, Marchal, Kathleen
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2690998/
https://www.ncbi.nlm.nih.gov/pubmed/19265557
http://dx.doi.org/10.1186/gb-2009-10-3-r27
Descripción
Sumario: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.

Ejemplares similares