title: Reconstruction of microbial transcriptional regulatory networks.
abstract: Although metabolic networks can be readily reconstructed through comparative genomics, the reconstruction of regulatory networks has been hindered by the relatively low level of evolutionary conservation of their molecular components. Recent developments in experimental techniques have allowed the generation of vast amounts of data related to regulatory networks. This data together with literature-derived knowledge has opened the way for genome-scale reconstruction of transcriptional regulatory networks. Large-scale regulatory network reconstructions can be converted to in silico models that allow systematic analysis of network behavior in response to changes in environmental conditions. These models can further be combined with genome-scale metabolic models to build integrated models of cellular function including both metabolism and its regulation.
authors.affiliation: Department of Bioengineering, Bioinformatics Graduate Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412, USA.
authors.forename: Markus J
authors.initials: MJ
authors.lastname: Herrgård
authors.forename: Markus W
authors.initials: MW
authors.lastname: Covert
authors.forename: Bernhard Ø
authors.initials: BØ
authors.lastname: Palsson
mesh_terms: D001419:Bacteria / Q000235:genetics* / Q000378:metabolism*; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D030562:Databases, Protein; D019143:Evolution, Molecular; D020869:Gene Expression Profiling / Q000379:methods*; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology*; D016680:Genome, Bacterial; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D014158:Transcription, Genetic / Q000502:physiology*
chemical_list: D001426:Bacterial Proteins