OperonDB: A comprehensive database of predicted operons in microbial genomes

Mihaela Pertea; Kunmi Ayanbule; Megan Smedinghoff; Steven L. Salzberg

doi:10.1093/nar/gkn784

OperonDB: A comprehensive database of predicted operons in microbial genomes

Mihaela Pertea, Kunmi Ayanbule, Megan Smedinghoff, Steven L. Salzberg

Research output: Contribution to journal › Article › peer-review

72 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	D479-D482
Journal	Nucleic acids research
Volume	37
Issue number	SUPPL. 1
DOIs	https://doi.org/10.1093/nar/gkn784
State	Published - 2009
Externally published	Yes

ASJC Scopus subject areas

Genetics

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title = "OperonDB: A comprehensive database of predicted operons in microbial genomes",

abstract = "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.",

author = "Mihaela Pertea and Kunmi Ayanbule and Megan Smedinghoff and Salzberg, {Steven L.}",

note = "Funding Information: National Institutes of Health (R01-LM006845 and R01-GM083873). Funding for open access charge: National Institutes of Health (R01-LM006845 and R01-GM083873).",

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AU - Ayanbule, Kunmi

AU - Smedinghoff, Megan

AU - Salzberg, Steven L.

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AB - 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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OperonDB: A comprehensive database of predicted operons in microbial genomes

Abstract

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