Peptide vaccine models using statistical data mining
DSpace at IIT Bombay
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Title |
Peptide vaccine models using statistical data mining
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Creator |
JOSHI, RR
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Subject |
b-cell epitopes
prediction network recognition b-cell epitope paratope logistic regression sequence-alignment solvent accessibility heuristics |
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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.
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Publisher |
BENTHAM SCIENCE PUBL LTD
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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 |
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Type |
Article
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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 |
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Language |
en
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