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Bioinformatics. 2007 Dec 1;23(23):3241-3. Epub 2007 Jun 28.

CASVM: web server for SVM-based prediction of caspase substrates cleavage sites.

Author information

1
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Abstract

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

PMID:
17599937
DOI:
10.1093/bioinformatics/btm334
[Indexed for MEDLINE]
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