RegulonDB statistics

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Citations per year

Number of citations per year for the bioinformatics software tool RegulonDB
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Tool usage distribution map

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Associated diseases

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Protocols

RegulonDB specifications

Information


Unique identifier OMICS_01868
Name RegulonDB
Restrictions to use None
Community driven No
Data access File download, Browse
User data submission Not allowed
Version 10.5
Maintained Yes
Wikipedia https://en.wikipedia.org/wiki/RegulonDB

Taxon


  • Bacteria
    • Escherichia coli

Maintainer


  • person_outline Julio Collado-Vides

Additional information


http://regulondb.ccg.unam.mx/central_panel_menu/doc_and_help_menu.jsp

Publications for RegulonDB

RegulonDB citations

 (67)
library_books

A comprehensive evaluation of module detection methods for gene expression data

2018
Nat Commun
PMCID: 5854612
PMID: 29545622
DOI: 10.1038/s41467-018-03424-4

[…] SEEK GPL5175 dataset is an aggregation of public datasets using the GPL5175 microarray platform and was retrieved from seek.princeton.edu.We generated two synthetic datasets starting from the E. coli regulondb network and yeast MacIsaac network (both described above) using GeneNetWeaver. This network simulator models the gene regulation using a detailed thermodynamic model and simulates this model […]

library_books

PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli

2018
Sci Rep
PMCID: 5772556
PMID: 29343727
DOI: 10.1038/s41598-017-18648-5

[…] A dataset (named CRPS) consisting of 169 CRP-binding sites with regulatory roles supported by strong evidence was established to train and evaluate this work. The CRPS dataset was retrieved from the RegulonDB database (version 8.8), containing up-to-date information on E. coli. The retrieval procedure of CRPS was given as follows:Step 1:  Retrieve TF-binding sites where the “TF name” column was a […]

library_books

Systematic identification of novel regulatory interactions controlling biofilm formation in the bacterium Escherichia coli

2017
Sci Rep
PMCID: 5711951
PMID: 29196655
DOI: 10.1038/s41598-017-17114-6

[…] To reconstruct the flagella-biofilm regulatory network, information regarding the transcriptional regulation of E. coli was gathered from scientific articles and compiled with that from RegulonDB and KEGG DB, and from the extensive analysis of the literature. We used only experimentally validated interaction and not large-scale data or computational predictions. The resulting network […]

library_books

First steps in automatic summarization of transcription factor properties for RegulonDB: classification of sentences about structural domains and regulated processes

2017
PMCID: 5737074
PMID: 29220462
DOI: 10.1093/database/bax070

[…] ranscription Factor Prediction Database () (http://www.transcriptionfactor.org/index.cgi?Download) and extracted domain family names. In addition, we obtained all of the TF evolutionary families from RegulonDB () (http://regulondb.ccg.unam.mx/) and all of the bacterial families of proteins from Interpro () (https://www.ebi.ac.uk/interpro/). To obtain a list of molecular functions, we extracted GO […]

library_books

Lighting up yeast cell factories by transcription factor based biosensors

2017
FEMS Yeast Res
PMCID: 5812511
PMID: 28961766
DOI: 10.1093/femsyr/fox076

[…] eir operators (Strachan et al.).Alternatively, it is also possible to use different predictive tools and databases for transcriptional regulation in order to identify aTFs of interest. One example is RegulonDB (http://regulondb.ccg.unam.mx), which contains a list of TFs in E. coli with information on operator sequences, and the genes regulated by the TF (Gama-Castro et al.). RegulonDB also allows […]

library_books

Optimizing complex phenotypes through model guided multiplex genome engineering

2017
Genome Biol
PMCID: 5445303
PMID: 28545477
DOI: 10.1186/s13059-017-1217-z

[…] at caused a greater than tenfold change in predicted expression were included for testing. Finally, we also considered mutations that overlapped promoters of essential genes based on annotations from RegulonDB [].The 20 UAG-reversion targets were chosen when UAGs occurred in essential genes, introduced non-synonymous changes in overlapping genes, or disrupted a predicted regulatory feature as abov […]


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RegulonDB institution(s)
Centro de Ciencias Genomicas, Universidad Nacional Autonoma de Mexico, Cuernavaca, Mexico; Department of Biomedical Engineering, Boston University, Boston, MA, USA
RegulonDB funding source(s)
Supported by Universidad Nacional Autonoma de Mexico; National Institute of General Medical Sciences of the National Institutes of Health [R01GM110597, U24GM077678].

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