The National Microbial Pathogen Database Resource (NMPDR): A genomics platform based on subsystem annotation

Leslie Klis McNeil, Claudia Reich, Ramy K. Aziz, Daniela Bartels, Matthew Cohoon, Terry Disz, Robert A. Edwards, Svetlana Gerdes, Kaitlyn Hwang, Michael Kubal, Gohar Rem Margaryan, Folker Meyer, William Mihalo, Gary J. Olsen, Robert Olson, Andrei Osterman, Daniel Paarmann, Tobias Paczian, Bruce Parrello, Gordon D. PuschDmitry A. Rodionov, Xinghua Shi, Olga Vassieva, Veronika Vonstein, Olga Zagnitko, Fangfang Xia, Jenifer Zinner, Ross Overbeek, Rick Stevens

Research output: Contribution to journalArticlepeer-review

76 Citations (Scopus)

Abstract

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of ∼50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.

Original languageEnglish
Pages (from-to)D347-D353
JournalNucleic Acids Research
Volume35
Issue numberSUPPL. 1
DOIs
Publication statusPublished - Jan 2007
Externally publishedYes

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