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Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/3183
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dc.contributor.authorAlshafah, Samara Aen_US
dc.contributor.authorBeljanski, Milošen_US
dc.contributor.authorMitić, Nenaden_US
dc.date.accessioned2026-02-24T17:02:01Z-
dc.date.available2026-02-24T17:02:01Z-
dc.date.issued2025-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/3183-
dc.description.abstractCorrect recognition of sequence characteristics is one of the most important steps in bioinformatics. The paper presents a method for the characterization of surface glycoprotein in different viruses. The method uses amino-acid and nucleotide repeat sequences to form a virus/protein profile that is used to characterize and predict the type of protein. Based on a set of characteristic repetitive sequences, a classification model for predicting the type of virus was constructed.en_US
dc.language.isoenen_US
dc.publisherBeograd : IPSI BGDen_US
dc.relation.ispartofIPSI BgD Transactions on Internet Researchen_US
dc.subjectclassificationen_US
dc.subjectcoronavirusen_US
dc.subjectfiloviridaeen_US
dc.subjectrepeat sequencesen_US
dc.subjectsurface glycoproteinen_US
dc.titleSurface Glycoprotein Classification Using Repeat Sequencesen_US
dc.typeArticleen_US
dc.identifier.isi001490644200009-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.issn1820-4503en_US
dc.description.rankM23en_US
dc.relation.firstpage100en_US
dc.relation.lastpage106en_US
dc.relation.volume21‚‚en_US
dc.relation.issue2en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptInformatics and Computer Science-
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