RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

P. S. Novichkov, D. A. Rodionov, E. D. Stavrovskaya, E. S. Novichkova, A. E. Kazakov, M. S. Gelfand, A. P. Arkin, A. A. Mironov, I. Dubchak
2010 Nucleic Acids Research  
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
more » ... ly. 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 Downloaded from Figure 4. Interactive workspace of the RegPredict web server. Example shows the main output obtained by scanning nine Shewanella genomes with PWM for the NagR transcription factor. Prioritized clusters of co-regulated orthologous operons (CRONs) are listed in the left panel table. Genomic context and summary gene function information for the first selected CRON are shown in the central and right panels, respectively. Detailed genomic information for the selected NagR-regulated operon in S. oneidensis MR-1 is shown in the bottom panel.
doi:10.1093/nar/gkq531 pmid:20542910 pmcid:PMC2896116 fatcat:hifo7rl75vf7db2x5ngckp5gmu