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RECOVIR Software for Identifying VirusesMost single-stranded RNA (ssRNA) viruses mutate rapidly to generate a large number of strains with highly divergent capsid sequences. Determining the capsid residues or nucleotides that uniquely characterize these strains is critical in understanding the strain diversity of these viruses. RECOVIR (an acronym for "recognize viruses") software predicts the strains of some ssRNA viruses from their limited sequence data. Novel phylogenetic-tree-based databases of protein or nucleic acid residues that uniquely characterize these virus strains are created. Strains of input virus sequences (partial or complete) are predicted through residue-wise comparisons with the databases. RECOVIR uses unique characterizing residues to identify automatically strains of partial or complete capsid sequences of picorna and caliciviruses, two of the most highly diverse ssRNA virus families. Partition-wise comparisons of the database residues with the corresponding residues of more than 300 complete and partial sequences of these viruses resulted in correct strain identification for all of these sequences. This study shows the feasibility of creating databases of hitherto unknown residues uniquely characterizing the capsid sequences of two of the most highly divergent ssRNA virus families. These databases enable automated strain identification from partial or complete capsid sequences of these human and animal pathogens.
Document ID
20130014517
Acquisition Source
Headquarters
Document Type
Other - NASA Tech Brief
Authors
Chakravarty, Sugoto
(Houston Univ. Houston, TX, United States)
Fox, George E.
(Houston Univ. Houston, TX, United States)
Zhu, Dianhui
(Houston Univ. Houston, TX, United States)
Date Acquired
November 26, 2013
Publication Date
December 1, 2013
Publication Information
Publication: NASA Tech Briefs, December 2013
Subject Category
Man/System Technology And Life Support
Life Sciences (General)
Report/Patent Number
MSC-24358-1
Distribution Limits
Public
Copyright
Public Use Permitted.
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