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The rule based classification models for MHC binding prediction and identification of the most relevant physicochemical properties for the individual allele
dc.creator | Jandrlić, Davorka | |
dc.date.accessioned | 2022-09-19T17:49:28Z | |
dc.date.available | 2022-09-19T17:49:28Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 1450-7226 | |
dc.identifier.uri | https://machinery.mas.bg.ac.rs/handle/123456789/2261 | |
dc.description.abstract | Binding of proteolyzed fragments of proteins to MHC molecules is essential and the most selective step that determines T-cell epitopes. Therefore, the prediction of MHC-peptide binding is principal for anticipating potential T cell epitopes and is of immense relevance in vaccine design. Despite numerous methods for predicting MHC binding ligands, there still exist limitations that affect the reliability of a prevailing number of methods. Certain important methods based on physicochemical properties have very low reported accuracy. The aim of this paper is to present a new approach of extracting the most important physicochemical properties that influence the classification of MHC-binding ligands. In this study, we have developed rule based classification models which take into account the physicochemical properties of amino acids and their frequencies. The models use k-means clustering technique for extracting the relevant physicochemical properties. The results of the study indicate that the physicochemical properties of amino acids contribute significantly to the peptide-binding and that the different alleles are characterized by a different set of the physicochemical properties. | en |
dc.publisher | Univerzitet u Prištini - Prirodno-matematički fakultet, Kosovska Mitrovica | |
dc.relation | info:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/174002/RS// | |
dc.rights | openAccess | |
dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ | |
dc.source | The University Thought - Publication in Natural Sciences | |
dc.subject | The rule based classification | en |
dc.subject | MHC - peptide binding | en |
dc.subject | K - mean clustering | en |
dc.title | The rule based classification models for MHC binding prediction and identification of the most relevant physicochemical properties for the individual allele | en |
dc.type | article | |
dc.rights.license | BY-SA | |
dc.citation.epage | 66 | |
dc.citation.issue | 1 | |
dc.citation.other | 6(1): 60-66 | |
dc.citation.rank | M24 | |
dc.citation.spage | 60 | |
dc.citation.volume | 6 | |
dc.identifier.doi | 10.5937/univtho6-10768 | |
dc.identifier.fulltext | http://machinery.mas.bg.ac.rs/bitstream/id/1015/2258.pdf | |
dc.type.version | publishedVersion |