[show abstract][hide abstract] ABSTRACT: Web services application programming interface (API) was developed to provide a programmatic access to the regulatory interactions accumulated in the RegPrecise database (http://regprecise.lbl.gov), a core resource on transcriptional regulation for the microbial domain of the Department of Energy (DOE) Systems Biology Knowledgebase. RegPrecise captures and visualize regulogs, sets of genes controlled by orthologous regulators in several closely related bacterial genomes, that were reconstructed by comparative genomics. The current release of RegPrecise 2.0 includes >1400 regulogs controlled either by protein transcription factors or by conserved ribonucleic acid regulatory motifs in >250 genomes from 24 taxonomic groups of bacteria. The reference regulons accumulated in RegPrecise can serve as a basis for automatic annotation of regulatory interactions in newly sequenced genomes. The developed API provides an efficient access to the RegPrecise data by a comprehensive set of 14 web service resources. The RegPrecise web services API is freely accessible at http://regprecise.lbl.gov/RegPrecise/services.jsp with no login requirements.
Nucleic Acids Research 06/2012; 40(Web Server issue):W604-8. · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.
Nucleic Acids Research 07/2010; 38(Web Server issue):W299-307. · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: The RegPrecise database (http://regprecise.lbl.gov) was developed for capturing, visualization and analysis of predicted transcription factor regulons in prokaryotes that were reconstructed and manually curated by utilizing the comparative genomic approach. A significant number of high-quality inferences of transcriptional regulatory interactions have been already accumulated for diverse taxonomic groups of bacteria. The reconstructed regulons include transcription factors, their cognate DNA motifs and regulated genes/operons linked to the candidate transcription factor binding sites. The RegPrecise allows for browsing the regulon collections for: (i) conservation of DNA binding sites and regulated genes for a particular regulon across diverse taxonomic lineages; (ii) sets of regulons for a family of transcription factors; (iii) repertoire of regulons in a particular taxonomic group of species; (iv) regulons associated with a metabolic pathway or a biological process in various genomes. The initial release of the database includes approximately 11,500 candidate binding sites for approximately 400 orthologous groups of transcription factors from over 350 prokaryotic genomes. Majority of these data are represented by genome-wide regulon reconstructions in Shewanella and Streptococcus genera and a large-scale prediction of regulons for the LacI family of transcription factors. Another section in the database represents the results of accurate regulon propagation to the closely related genomes.
Nucleic Acids Research 11/2009; 38(Database issue):D111-8. · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: Recognition of transcription regulatory sites in bacterial genomes is a notoriously difficult problem. There are no algorithms capable of making reliable predictions even for well-studied sites such as the CRP (cyclic AMP receptor protein) box. However, availability of complete bacterial genomes makes it possible to make reliable predictions with bad rules. This comparative approach is based on the assumption that sets of co-regulated genes are conserved in related bacteria. Thus true sites occur upstream of orthologous genes, whereas false candidates are scattered at random. This means not only that knowledge about regulation in well-studied genomes can be transferred to newly sequenced ones, but also that new members of regulons can be found. This paper reviews several recent studies. In particular, a detailed analysis of catabolite repression in gamma-purple bacteria is presented.
Briefings in Bioinformatics 12/2000; 1(4):357-71. · 5.30 Impact Factor