Format

Send to

Choose Destination
Nucleic Acids Res. 2016 Jan 4;44(D1):D133-43. doi: 10.1093/nar/gkv1156. Epub 2015 Nov 2.

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond.

Author information

1
Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, Mexico.
2
UMR_S 1090 TAGC, INSERM, Marseille, 13000 France.
3
Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Boulevard Juriquilla 3001, Juriquilla 76230, Santiago de Querétaro, QRO, Mexico.
4
Departamento de Microbiologia Molecular, IBT, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62100, Mexico.
5
Institute of Computational Linguistics, University of Zurich, Binzmühlestrasse 14, CH-8050 Zurich, Switzerland.
6
Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, Mexico collado@ccg.unam.mx.

Abstract

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for 'neighborhood' genes to known operons and regulons, and computational developments.

PMID:
26527724
PMCID:
PMC4702833
DOI:
10.1093/nar/gkv1156
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center