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NAR Molecular Biology Database Collection entry number 1207
Liu, B.2, Pop, M.1,2
1Department of Computer Science, University of Maryland, College Park, MD 20742, USA.2Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA.

Database Description

The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database - the Antibiotic Resistance Genes Database (ARDB) - unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG, and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13,293 genes, 377 resistance types, 257 antibiotics, 632 genomes, 933 species and 124 genera.

Recent Developments

Several analyses provided by our database now also produce output in tab-delimited spreadsheet format (with .xls extension for easy access from OpenOffice or MS Office). Such output is now available for comparisons of resistance profiles between two or more organisms in our database, as well as for genome annotation. Several of the algorithms underlying our database have been improved resulting in faster access and eliminating browser time-outs for the more intensive queries.

Go to the abstract in the NAR 2009 Database Issue.
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