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Peptide vaccine models using statistical data mining

DSpace at IIT Bombay

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Field Value
 
Title Peptide vaccine models using statistical data mining
 
Creator JOSHI, RR
 
Subject b-cell epitopes
prediction
network
recognition
b-cell epitope
paratope
logistic regression
sequence-alignment
solvent accessibility
heuristics
 
Description Design and synthesis of peptide vaccines is of significant pharmaceutical importance. A knowledge based statistical model is fitted here for prediction of binding of an antigenic site of a protein or a B-cell epitope on a CDR (complementarity determining region) of an immunoglobulin. Linear analogues of the 3D structure of the epitopes are computed using this model. Extension for prediction of peptide epitopes from the protein sequence alone is also presented. Validation results show promising potential of this approach in computer-aided peptide vaccine production. The computed probabilities of binding also provide a pioneering approach for ab-initio prediction of 'potency' of protein or peptide vaccines modeled by this method.
 
Publisher BENTHAM SCIENCE PUBL LTD
 
Date 2011-07-18T23:57:16Z
2011-12-26T12:50:54Z
2011-12-27T05:37:05Z
2011-07-18T23:57:16Z
2011-12-26T12:50:54Z
2011-12-27T05:37:05Z
2007
 
Type Article
 
Identifier PROTEIN AND PEPTIDE LETTERS, 14(6), 536-542
0929-8665
http://dspace.library.iitb.ac.in/xmlui/handle/10054/5109
http://hdl.handle.net/10054/5109
 
Language en