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Tractor_DB (version 2.0): a database of regulatory interactions in gamma-proteobacterial genomes.


ABSTRACT: The version 2.0 of Tractor_DB is now accessible at its three international mirrors: www.bioinfo.cu/Tractor_DB, www.tractor.lncc.br and http://www.ccg.unam.mx/tractorDB. This database contains a collection of computationally predicted Transcription Factors' binding sites in gamma-proteobacterial genomes. These data should aid researchers in the design of microarray experiments and the interpretation of their results. They should also facilitate studies of Comparative Genomics of the regulatory networks of this group of organisms. In this paper we describe the main improvements incorporated to the database in the past year and a half which include incorporating information on the regulatory networks of 13-increasing to 30-new gamma-proteobacteria and developing a new computational strategy to complement the putative sites identified by the original weight matrix-based approach. We have also added dynamically generated navigation tabs to the navigation interfaces. Moreover, we developed a new interface that allows users to directly retrieve information on the conservation of regulatory interactions in the 30 genomes included in the database by navigating a map that represents a core of the known Escherichia coli regulatory network.

SUBMITTER: Perez AG 

PROVIDER: S-EPMC1669740 | biostudies-literature | 2007 Jan

REPOSITORIES: biostudies-literature

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Tractor_DB (version 2.0): a database of regulatory interactions in gamma-proteobacterial genomes.

Pérez Abel González AG   Angarica Vladimir Espinosa VE   Vasconcelos Ana Tereza R AT   Collado-Vides Julio J  

Nucleic acids research 20061106 Database issue


The version 2.0 of Tractor_DB is now accessible at its three international mirrors: www.bioinfo.cu/Tractor_DB, www.tractor.lncc.br and http://www.ccg.unam.mx/tractorDB. This database contains a collection of computationally predicted Transcription Factors' binding sites in gamma-proteobacterial genomes. These data should aid researchers in the design of microarray experiments and the interpretation of their results. They should also facilitate studies of Comparative Genomics of the regulatory ne  ...[more]

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