Reference : Complementing computationally predicted regulatory sites in Tractor_DB using a patter...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/16687
Complementing computationally predicted regulatory sites in Tractor_DB using a pattern matching approach.
English
Guia, Marylens Hernandez [National Bioinformatics Center, Industria y San José, Capitolio Nacional, CP. 10200, Habana Vieja, Habana, Cuba]
Perez, Abel Gonzalez [National Bioinformatics Center, Industria y San José, Capitolio Nacional, CP. 10200, Habana Vieja, Habana, Cuba]
Espinosa Angarica, Vladimir mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Vasconcelos, Ana T. [National Laboratory for Scientific Computing, Avenue Getulio Vargas 333, Quitandinha, CEP 25651-075, Petropolis, Rio de Janeiro, Brazil]
Collado-Vides, Julio [Center of Genomics, UNAM, AP 565-A Cuernavaca, CP. 62100, Morelos, Mexico]
2005
In silico biology
5
2
209-19
Yes (verified by ORBilu)
International
1386-6338
Netherlands
[en] transcriptional regulatory networks ; TF-binding-site prediction ; regulon ; gamma-proteobacteria
[en] Prokaryotic genomes annotation has focused on genes location and function. The lack of regulatory information has limited the knowledge on cellular transcriptional regulatory networks. However, as more phylogenetically close genomes are sequenced and annotated, the implementation of phylogenetic footprinting strategies for the recognition of regulators and their regulons becomes more important. In this paper we describe a comparative genomics approach to the prediction of new gamma-proteobacterial regulon members. We take advantage of the phylogenetic proximity of Escherichia coli and other 16 organisms of this subdivision and the intensive search of the space sequence provided by a pattern-matching strategy. Using this approach we complement predictions of regulatory sites made using statistical models currently stored in Tractor_DB, and increase the number of transcriptional regulators with predicted binding sites up to 86. All these computational predictions may be reached at Tractor_DB (www.bioinfo.cu/Tractor_DB, www.tractor.lncc.br, www.ccg.unam.mx/Computational_Genomics/tractorDB/). We also take a first step in this paper towards the assessment of the conservation of the architecture of the regulatory network in the gamma-proteobacteria through evaluating the conservation of the overall connectivity of the network.
Researchers ; Students
http://hdl.handle.net/10993/16687
http://iospress.metapress.com/content/8y6ay58ak8t9wdh6/?genre=article&issn=1386-6338&volume=5&issue=2&spage=209

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