The RegPredict a computational platform supporting genomic reconstruction of transcriptional regulons in groups of closely related prokaryotic genomes. Regulons are described as gene sets with shared regulatory sites. The platform combines specialized software tools with manual curation of regulons and implements two main strategies of regulon inference: Rregulon Inference by Known Position Weight Matrix (PWM) and De Novo Regulon Inference.
Regulon Inference by Known PWM
- RegPredict provides a comprehensive collection of manually curated PWMs from several resources, such as RegTransBase, RegulonDB, RegPrecise.
- At the first step, all genomes under analysis are scanned by selected PWM, and candidate transcription factor binding sites are identified.
- At the second step, clusters of co-regulated orthologous operons are computed, ranked, and provided as an output for manual curation using highly interactive graphical user interface. The top ranked operon clusters are the best candidates for true members of regulon.
De Novo Regulon Inference
- The input of this module is a set of functionally linked genes that can be potential members of regulon. The module allows searching motif profiles in upstream regions of selected genes considering several different types of motif simultaneously (palindromes of different length, direct repeats, etc.).
- The list of candidate motif profiles, ranked by information content is represented as an output for the subsequent testing. This module is tightly integrated with the module based on the known PWM, and each motif profile can be immediately tested by scanning genomes and analysis of regulon member candidates.
Related Web Resources
Manually curated database for capturing, visualization and analysis of transcription factor regulons that were reconstructed by the comparative genomic approach in a wide variety of prokaryotic genomes
Manually curated database of regulatory interactions in prokaryotes, captures the knowledge in published scientific literature using a controlled vocabulary