Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/325
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dc.contributor.authorMarovac, Ulfeta A.en_US
dc.contributor.authorMitić, Nenaden_US
dc.date.accessioned2022-08-09T12:45:54Z-
dc.date.available2022-08-09T12:45:54Z-
dc.date.issued2015-01-01-
dc.identifier.issn03406253-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/325-
dc.description.abstractThe classification of proteins categorized in the Cluster of Orthologous Groups (COGs) is important for better understanding of biological processes, as well as for various pathological conditions in human and other organisms. In this paper, a model for classification of proteins in the COG categories based on characteristic amino acid n-grams is proposed. A novel method, based on Boolean algebra, for extracting n-grams which characterize proteins belonging to a certain COG category is presented. The presented method significantly reduces the number of processed n-grams, which implies the reduction of required storage space and processing time. The obtained results show that the proteins of a certain COG category contain n-grams which satisfy specific patterns; such n-grams are unique, related to different COG categories. The model for classification based on the proposed method assigns a correct COG category to a protein with the confidence of 96%.en_US
dc.relation.ispartofMatchen_US
dc.titleN-gram analysis of COG categorized protein sequencesen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-84943241299-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84943241299-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.firstpage575en_US
dc.relation.lastpage590en_US
dc.relation.volume74en_US
dc.relation.issue3en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeArticle-
crisitem.author.deptInformatics and Computer Science-
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