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CytoPred: a server for prediction and classification of cytokines.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title CytoPred: a server for prediction and classification of cytokines.
 
Creator Lata, Sneh
Raghava, G.P.S.
 
Subject QH301 Biology
 
Description 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.
 
Publisher Oxford University Press
 
Date 2008-04
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/613/1/raghava08.pdf
Lata, Sneh and Raghava, G.P.S. (2008) CytoPred: a server for prediction and classification of cytokines. Protein engineering, design & selection : PEDS, 21 (4). pp. 279-282. ISSN 1741-0126
 
Relation http://peds.oxfordjournals.org/content/21/4/279.full.pdf+html
http://crdd.osdd.net/open/613/