Bioinformatics Advance Access published online on September 3, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti015
Bioinformatics © Oxford University Press 2004; all rights reserved
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1 The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850
* To whom correspondence should be addressed.
Motivation: The presence or absence of metabolic pathways, and structures provides context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. Results: We have created Genome Properties to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny, and computational analyses. The results of searches using Hidden Markov Models (HMMs) allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports, and other forms of evidence. Genome Properties has been applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. Availability: Genome Properties can be found at http://www.tigr.org/Genome_Properties.
Revised July 9, 2004
Accepted August 5, 2004
Article
Genome properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics
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