dc.contributor.author |
Polatkan, Aydın Can
|
|
dc.contributor.author |
Oğul, Hasan
|
|
dc.contributor.author |
Sever, Hayri
|
|
dc.date.accessioned |
2020-04-27T21:05:32Z |
|
dc.date.available |
2020-04-27T21:05:32Z |
|
dc.date.issued |
2008 |
|
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). |
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dc.identifier.issn |
978-076953191-5 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.12416/3463 |
|
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. |
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dc.language.iso |
eng |
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dc.publisher |
IEEE |
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dc.relation.isversionof |
10.1109/BIOTECHNO.2008.23 |
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dc.rights |
info:eu-repo/semantics/closedAccess |
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dc.subject |
Bioinformatics |
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dc.subject |
Proteins |
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dc.subject |
Remote Homology |
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dc.title |
A Data Fusion Approach In Protein Homology Detection |
tr_TR |
dc.type |
bookPart |
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dc.relation.journal |
Proceedings - International Conference On Biocomputation, Bioinformatics, and Biomedical Technologies, Bıotechno 2008 |
tr_TR |
dc.contributor.authorID |
11916 |
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dc.identifier.startpage |
7 |
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dc.identifier.endpage |
12 |
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dc.contributor.department |
Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü |
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