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Bioinformatics Advance Access originally published online on June 28, 2007
Bioinformatics 2007 23(23):3241-3243; doi:10.1093/bioinformatics/btm334
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

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

Lawrence J.K. Wee 1, Tin Wee Tan 1 and Shoba Ranganathan 2,1,*

1Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore and 2Department of Chemistry and Biomolecular Sciences & Biotechnology Research Institute, Macquarie University, Sydney, Australia

*To whom correspondence should be addressed.


  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{at}mq.edu.au

Supplementary information: http://www.casbase.org/casvm/help/index.html

Associate Editor: Alex Bateman

Received on April 27, 2007; revised on June 12, 2007; accepted on June 17, 2007

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