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On Classification of PDZ Domains: A Computational Study

dc.contributor.authorBaleanu, Dumitru
dc.contributor.authorMemic, Adnan
dc.contributor.authorBaleanu, Dumitru
dc.contributor.authorID56389tr_TR
dc.date.accessioned2020-05-15T16:05:34Z
dc.date.available2020-05-15T16:05:34Z
dc.date.issued2013
dc.departmentÇankaya Üniversitesi, Fen Edebiyat Fakültesi, Matematik Bölümüen_US
dc.description.abstractOur goal in this present study is to introduce new wavelet based methods for differentiating and classifying Class I and Class II PDZ domains and compare the resulting signals. PDZ domains represent one of the most common protein homology regions playing key roles in several diseases. To perform the classification, we developed two methods. The first of our methods was comparable to the standard wavelet approaches while the second one surpasses it in recognition accuracy. Our models exhibited interesting results, and we anticipate that it can be used as a computational technique to screen out the misfit candidates and to reduce the search space, while achieving high classification and accuracy.en_US
dc.identifier.doi10.1155/2013/419485
dc.identifier.issn1024-123X
dc.identifier.issn1563-5147
dc.identifier.urihttps://hdl.handle.net/20.500.12416/3860
dc.language.isoenen_US
dc.publisherHindawi LTDen_US
dc.relation.ispartofMathematical Problems in Engineeringen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSpecificityen_US
dc.titleOn Classification of PDZ Domains: A Computational Studytr_TR
dc.titleOn Classification of Pdz Domains: a Computational Studyen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublicationf4fffe56-21da-4879-94f9-c55e12e4ff62
relation.isAuthorOfPublication.latestForDiscoveryf4fffe56-21da-4879-94f9-c55e12e4ff62

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