Dataset Information

RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12.

ABSTRACT: RegulonDB is a database on mechanisms of transcription regulation and operon organization in Escherichia coli K-12. The current version has considerably increased numbers of regulatory elements such as promoters, binding sites and terminators. The complete repertoire of known and predicted DNA-binding transcriptional regulators can be considered to be included in this version. The database now distinguishes different allosteric conformations of regulatory proteins indicating the one active in binding and regulating the different promoters. A new set of operon predictions has been incorporated. The relational design has been modified accordingly. Furthermore, a major improvement is a graphic display enabling browsing of the database with a Java-based graphic user interface with three zoom-levels connected to properties of each chromosomal element. The purpose of these modifications is to make RegulonDB a useful tool and control set for transcriptome experiments. RegulonDB can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/++ +regulondb/

SUBMITTER: Salgado H

PROVIDER: S-EPMC29794 | biostudies-literature | 2001 Jan

REPOSITORIES: biostudies-literature

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Publications

RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12.

Salgado H H Santos-Zavaleta A A Gama-Castro S S Millán-Zárate D D Díaz-Peredo E E Sánchez-Solano F F Pérez-Rueda E E Bonavides-Martínez C C Collado-Vides J J

Nucleic acids research 20010101 1

RegulonDB is a database on mechanisms of transcription regulation and operon organization in Escherichia coli K-12. The current version has considerably increased numbers of regulatory elements such as promoters, binding sites and terminators. The complete repertoire of known and predicted DNA-binding transcriptional regulators can be considered to be included in this version. The database now distinguishes different allosteric conformations of regulatory proteins indicating the one active in bi ...[more]

PMID: 11125053

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Project description:Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

Dataset Information

RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12.

Publications

RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12.

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