RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more
By Heladia Salgado, Martín Peralta-Gil, S. Gama-Castro, Alberto Santos-Zavaleta, Luis Muñiz-Rascado, J. García-Sotelo, V. Weiss, Hilda Solano-Lira, Irma Martínez-Flores, A. Medina-Rivera and 17 more. Nucleic Acids Res., 2012
447 citations recorded by the source corpus.
This article summarizes our progress with RegulonDB (http://regulondb.ccg.unam.mx/) during the past 2 years. We have kept up-to-date the knowledge from the published literature regarding transcriptional regulation in Escherichia coli K-12. We have maintained and expanded our curation efforts to improve the breadth and quality of the encoded experimental knowledge, and we have implemented criteria for the quality of our computational predictions. Regulatory phrases now provide high-level descriptions of regulatory regions. We expanded the assignment of quality to various sources of evidence, particularly for knowledge generated through high-throughput (HT) technology. Based on our analysis of most relevant methods, we defined rules for determining the quality of evidence when multiple independent sources support an entry. With this latest release of RegulonDB, we present a new highly reliable larger collection of transcription start sites, a result of our experimental HT genome-wide efforts. These improvements, together with several novel enhancements (the tracks display, uploading format and curational guidelines), address the challenges of incorporating HT-generated knowledge into RegulonDB. Information on the evolutionary conservation of regulatory elements is also available now. Altogether, RegulonDB version 8.0 is a much better home for integrating knowledge on gene regulation from the sources of information currently available.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/11745eab24a8d8740dd1ecb60e1ca15ee02ec89a
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In Molecular Biology
Citations in the corpus
- RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond (2015, methodology): “As mentioned in the ‘Introduction’ section, through the years we have gradually expanded both the content and level of detail of the biological data as well as the diverse types of experimental and bioinformatics sources of knowledge that nurture our understanding of gene regulation in E.coli K-12.”
- RegulonDB v 10.5: tackling challenges to unify classic and high throughput knowledge of gene regulation in E. coli K-12 (2018, background): “We have progressed in expanding our curation to include publications based on HT technologies (4,17,18).”