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      Operon-mapper: a web server for precise operon identification in bacterial and archaeal genomes

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          Abstract

          Summary

          Operon-mapper is a web server that accurately, easily and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences.

          Availability and implementation

          http://biocomputo.ibt.unam.mx/operon_mapper/

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          DOOR: a database for prokaryotic operons

          Fenglou Mao, PhuongAn Dam, Jacky Chou … (2009)
          We present a database DOOR (Database for prOkaryotic OpeRons) containing computationally predicted operons of all the sequenced prokaryotic genomes. All the operons in DOOR are predicted using our own prediction program, which was ranked to be the best among 14 operon prediction programs by a recent independent review. Currently, the DOOR database contains operons for 675 prokaryotic genomes, and supports a number of search capabilities to facilitate easy access and utilization of the information stored in it. Querying the database: the database provides a search capability for a user to find desired operons and associated information through multiple querying methods. Searching for similar operons: the database provides a search capability for a user to find operons that have similar composition and structure to a query operon. Prediction of cis-regulatory motifs: the database provides a capability for motif identification in the promoter regions of a user-specified group of possibly coregulated operons, using motif-finding tools. Operons for RNA genes: the database includes operons for RNA genes. OperonWiki: the database provides a wiki page (OperonWiki) to facilitate interactions between users and the developer of the database. We believe that DOOR provides a useful resource to many biologists working on bacteria and archaea, which can be accessed at http://csbl1.bmb.uga.edu/OperonDB.
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            ProOpDB: Prokaryotic Operon DataBase

            Blanca Taboada, Ricardo Ciria, Cristian E. Martinez-Guerrero … (2011)
            The Prokaryotic Operon DataBase (ProOpDB, http://operons.ibt.unam.mx/OperonPredictor) constitutes one of the most precise and complete repositories of operon predictions now available. Using our novel and highly accurate operon identification algorithm, we have predicted the operon structures of more than 1200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: (i) organism name, (ii) metabolic pathways, as defined by the KEGG database, (iii) gene orthology, as defined by the COG database, (iv) conserved protein domains, as defined by the Pfam database, (v) reference gene and (vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient method to select the most representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool to visualize their genomic context and retrieve the sequence of their corresponding 5′ regulatory regions, as well as the nucleotide or amino acid sequences of their genes.
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              OperonDB: a comprehensive database of predicted operons in microbial genomes

              Mihaela Pertea, Kunmi Ayanbule, Megan Smedinghoff … (2009)
              The fast pace of bacterial genome sequencing and the resulting dependence on highly automated annotation methods has driven the development of many genome-wide analysis tools. OperonDB, first released in 2001, is a database containing the results of a computational algorithm for locating operon structures in microbial genomes. OperonDB has grown from 34 genomes in its initial release to more than 500 genomes today. In addition to increasing the size of the database, we have re-designed our operon finding algorithm and improved its accuracy. The new database is updated regularly as additional genomes become available in public archives. OperonDB can be accessed at: http://operondb.cbcb.umd.edu
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                Author and article information

                Contributors
                John Hancock: Role: Associate Editor
                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (iso-abbrev): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date (Print): 01 December 2018
                Publication date (Electronic): 19 June 2018
                Publication date PMC-release: 19 June 2018
                Volume: 34
                Issue: 23
                Pages: 4118-4120
                Affiliations
                [1 ]Department of Developmental Genetics and Molecular Physiology, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
                [2 ]Department of Molecular Microbiology, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
                Author notes
                To whom correspondence should be addressed. E-mail: merino@ 123456ibt.unam.mx
                Author information
                http://orcid.org/0000-0002-7671-6959
                Article
                Publisher ID: bty496
                DOI: 10.1093/bioinformatics/bty496
                PMC ID: 6247939
                PubMed ID: 29931111
                SO-VID: 5f523eef-a657-448e-bf3e-5f96318aee10
                Copyright © © The Author(s) 2018. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Date received : 04 May 2018
                Date revision received : 10 June 2018
                Date accepted : 15 June 2018
                Page count
                Pages: 3
                Funding
                Funded by: Consejo Nacional de Ciencia y Tecnologia CONACyT
                Award ID: FC 2015-2 887
                Award ID: 235817
                Funded by: Dirección General de Asuntos del Personal Académico
                Award ID: IN202517
                Categories
                Subject: Applications Notes
                Subject: Genome Analysis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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