In:
Bioinformatics, Oxford University Press (OUP), Vol. 23, No. 23 ( 2007-12-01), p. 3241-3243
Abstract:
Summary: Caspases belong to a unique class of cysteine proteases which function as critical effectors of apoptosis, inflammation and other important cellular processes. Caspases cleave substrates at specific tetrapeptide sites after a highly conserved aspartic acid residue. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. We have recently developed a support vector machines (SVM) method to address this issue. Our algorithm achieved an accuracy ranging from 81.25 to 97.92%, making it one of the best methods currently available. CASVM is the web server implementation of our SVM algorithms, written in Perl and hosted on a Linux platform. The server can be used for predicting non-canonical caspase substrate cleavage sites. We have also included a relational database containing experimentally verified caspase substrates retrievable using accession IDs, keywords or sequence similarity. Availability: http://www.casbase.org/casvm/index.html Contact: shoba.ranganathan@mq.edu.au Supplementary information: http://www.casbase.org/casvm/help/index.html
Type of Medium:
Online Resource
ISSN:
1367-4811
,
1367-4803
DOI:
10.1093/bioinformatics/btm334
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2007
detail.hit.zdb_id:
1468345-3
SSG:
12
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