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dc.contributor.authorRay, Surajiten_US
dc.contributor.authorKepler, Thomas Ben_US
dc.date.accessioned2012-01-11T17:18:24Z
dc.date.available2012-01-11T17:18:24Z
dc.date.copyright2007en_US
dc.date.issued2007-10-29en_US
dc.identifier.citationRay, Surajit, Thomas B Kepler. "Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding" Immunome Research 3:9. (2007)en_US
dc.identifier.issn1745-7580en_US
dc.identifier.urihttp://hdl.handle.net/2144/3148
dc.description.abstractBACKGROUND. A key step in the development of an adaptive immune response to pathogens or vaccines is the binding of short peptides to molecules of the Major Histocompatibility Complex (MHC) for presentation to T lymphocytes, which are thereby activated and differentiate into effector and memory cells. The rational design of vaccines consists in part in the identification of appropriate peptides to effect this process. There are several algorithms currently in use for making such predictions, but these are limited to a small number of MHC molecules and have good but imperfect prediction power. RESULTS. We have undertaken an exploration of the power gained by taking advantage of a natural representation of the amino acids in terms of their biophysical properties. We used several well-known statistical classifiers using either a naive encoding of amino acids by name or an encoding by biophysical properties. In all cases, the encoding by biophysical properties leads to substantially lower misclassification error. CONCLUSION. Representation of amino acids using a few important bio-physio-chemical property provide a natural basis for representing peptides and greatly improves peptide-MHC class I binding prediction.en_US
dc.description.sponsorshipDuke University Center for Translational Research (5 P30 AI051445-03); Duke Epitope Discovery program (N01-A1-40082); Statistical and Mathematical Sciences Instituteen_US
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2007 Ray and Kepler; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.titleAmino Acid Biophysical Properties in the Statistical Prediction of Peptide-MHC Class I Bindingen_US
dc.typearticleen_US
dc.identifier.doi10.1186/1745-7580-3-9en_US
dc.identifier.pubmedid17967170en_US
dc.identifier.pmcid2186325en_US


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Copyright 2007 Ray and Kepler; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as Copyright 2007 Ray and Kepler; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.