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In Silico Biology 5, 0020 (2004); ©2004, Bioinformation Systems e.V.  

Complementing computationally predicted regulatory sites in Tractor_DB using a pattern matching approach

Marylens Hernández Guía1, Abel González Pérez1, Vladimir Espinosa Angarica1, Ana T. Vasconcelos2 and Julio Collado-Vides3,*

1 National Bioinformatics Center, Industria y San José, Capitolio Nacional, CP. 10200, Habana Vieja, Habana, Cuba
2 National Laboratory for Scientific Computing, Av. Getulio Vargas 333, Quitandinha, CEP 25651-075, Petropolis, Rio de Janeiro, Brazil
3 Center of Genomics, UNAM, Cuernavaca, Mexico. AP 565-A Cuernavaca, CP 62100, Morelos, Mexico

* Corresponding author; Email:

Edited by E. Wingender; received December 07, 2004; revised and accepted December 23, 2004; published January 04, 2005


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 (,, 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.

Keywords: transcriptional regulatory networks, comparative genomics, gamma-proteobacterial regulons