A Data Fusion Approach In Protein Homology Detection
| dc.authorscopusid | 24833640200 | |
| dc.authorscopusid | 14048917700 | |
| dc.authorscopusid | 55902090100 | |
| dc.contributor.author | Oğul, Hasan | |
| dc.contributor.author | Polatkan, A.C. | |
| dc.contributor.author | Oǧul, H. | |
| dc.contributor.author | Sever, Hayri | |
| dc.contributor.author | Sever, H. | |
| dc.contributor.authorID | 11916 | tr_TR |
| dc.contributor.other | Bilgisayar Mühendisliği | |
| dc.date.accessioned | 2020-04-27T21:05:32Z | |
| dc.date.available | 2020-04-27T21:05:32Z | |
| dc.date.issued | 2008 | |
| dc.department | Çankaya University | en_US |
| dc.department-temp | Polatkan A.C., Wilhelm-Schickard-Institute, Universität Tübingen, Department of Computer Engineering, Baskent University; Oǧul H., Department of Computer Engineering, Baskent University; Sever H., Department of Computer Engineering, Cankaya University | en_US |
| dc.description | IARIA | en_US |
| dc.description.abstract | The discriminative framework for protein remote homology detection based on support vector machines (SVMs) is reconstructed by the fusion of sequence based features. In this respect, n-peptide compositions are partitioned and fed into separate SVMs. The SVM outputs are evaluated with different techniques and tested to discern their ability for SCOP protein super family classification on a common benchmarking set. It reveals that the fusion approach leads to an improvement in prediction accuracy with a remarkable gain on computer memory usage. © 2008 IEEE. | en_US |
| dc.identifier.citation | Sever, Hayri; Polatkan, Aydin Can; Ogul, Hasan, "A Data Fusion Approach In Protein Homology Detection", Proceedings - International Conference On Biocomputation, Bioinformatics, and Biomedical Technologies, Bıotechno 2008, pp. 7-12, (2008). | en_US |
| dc.identifier.doi | 10.1109/BIOTECHNO.2008.23 | |
| dc.identifier.endpage | 12 | en_US |
| dc.identifier.isbn | 9780769531915 | |
| dc.identifier.scopus | 2-s2.0-52249124367 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 7 | en_US |
| dc.identifier.uri | https://doi.org/10.1109/BIOTECHNO.2008.23 | |
| dc.identifier.wosquality | N/A | |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | Proceedings - International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies, BIOTECHNO 2008 -- International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies, BIOTECHNO 2008 -- 29 June 2008 through 5 July 2008 -- Bucharest -- 73451 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.scopus.citedbyCount | 0 | |
| dc.title | A Data Fusion Approach In Protein Homology Detection | tr_TR |
| dc.title | A Data Fusion Approach in Protein Homology Detection | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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| relation.isAuthorOfPublication.latestForDiscovery | 285d39d9-5a1e-4e05-b1e4-631b1e965998 | |
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| relation.isOrgUnitOfPublication.latestForDiscovery | 12489df3-847d-4936-8339-f3d38607992f |
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