SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence.
DIR@IMTECH: CSIR-Institute of Microbial Technology
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Title |
SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence.
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Creator |
Bhasin, Manoj
Raghava, G.P.S. |
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Subject |
QR Microbiology
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Description |
Prediction of peptides binding with MHC class II allele HLA-DRB1(*)0401 can effectively reduce the number of experiments required for identifying helper T cell epitopes. This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1(*)0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique.
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Publisher |
Oxford University Press
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Date |
2004-02-12
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Type |
Article
PeerReviewed |
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Format |
application/pdf
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Identifier |
http://crdd.osdd.net/open/223/1/raghava2004.pdf
Bhasin, Manoj and Raghava, G.P.S. (2004) SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence. Bioinformatics (Oxford, England), 20 (3). pp. 421-3. ISSN 1367-4803 |
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Relation |
http://bioinformatics.oxfordjournals.org/content/20/3/421.long
http://crdd.osdd.net/open/223/ |
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