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PEDS Advance Access originally published online on February 20, 2008
Protein Engineering Design and Selection 2008 21(4):279-282; doi:10.1093/protein/gzn006
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Short communications

CytoPred: a server for prediction and classification of cytokines

Sneh Lata and G.P.S. Raghava1

Bioinformatics Centre, Institute of Microbial Technology, Chandigarh, India

1 To whom correspondence should be addressed. E-mail: raghava{at}imtech.res.in

Cytokines are messengers of immune system. They are small secreted proteins that mediate and regulate the immune system, inflammation and hematopoiesis. Recent studies have revealed important roles played by the cytokines in adjuvants as therapeutic targets and in cancer therapy. In this paper, an attempt has been made to predict this important class of proteins and classify further them into families and subfamilies. A PSI-BLAST+Support Vector Machine-based hybrid approach is adopted to develop the prediction methods. CytoPred is capable of predicting cytokines with an accuracy of 98.29%. The overall accuracy of classification of cytokines into four families and further classification into seven subfamilies is 99.77 and 97.24%, respectively. It has been shown by comparison that CytoPred performs better than the already existing CTKPred. A user-friendly server CytoPred has been developed and available at http://www.imtech.res.in/raghava/cytopred.

Keywords: cytokine/prediction/PSI-BLAST/SVM

Received December 6, 2007; revised December 6, 2007; accepted January 18, 2008.


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