BACKGROUND: The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. DESCRIPTION: CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CONCLUSION: CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.
BACKGROUND: The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. DESCRIPTION: CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CONCLUSION:CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.
Authors: Jörn Kalinowski; Brigitte Bathe; Daniela Bartels; Nicole Bischoff; Michael Bott; Andreas Burkovski; Nicole Dusch; Lothar Eggeling; Bernhard J Eikmanns; Lars Gaigalat; Alexander Goesmann; Michael Hartmann; Klaus Huthmacher; Reinhard Krämer; Burkhard Linke; Alice C McHardy; Folker Meyer; Bettina Möckel; Walter Pfefferle; Alfred Pühler; Daniel A Rey; Christian Rückert; Oliver Rupp; Hermann Sahm; Volker F Wendisch; Iris Wiegräbe; Andreas Tauch Journal: J Biotechnol Date: 2003-09-04 Impact factor: 3.307
Authors: Jacob Koehler; Chris Rawlings; Paul Verrier; Rowan Mitchell; Andre Skusa; Alexander Ruegg; Stephan Philippi Journal: In Silico Biol Date: 2005
Authors: Iris Brune; Nina Jochmann; Karina Brinkrolf; Andrea T Hüser; Robert Gerstmeir; Bernhard J Eikmanns; Jörn Kalinowski; Alfred Pühler; Andreas Tauch Journal: J Bacteriol Date: 2007-01-26 Impact factor: 3.490
Authors: Michael Dondrup; Stefan P Albaum; Thasso Griebel; Kolja Henckel; Sebastian Jünemann; Tim Kahlke; Christiane K Kleindt; Helge Küster; Burkhard Linke; Dominik Mertens; Virginie Mittard-Runte; Heiko Neuweger; Kai J Runte; Andreas Tauch; Felix Tille; Alfred Pühler; Alexander Goesmann Journal: BMC Bioinformatics Date: 2009-02-06 Impact factor: 3.169