Sever, H.Polatkan, A.C.Oǧul, H.06.01. Bilgisayar Mühendisliği06. Mühendislik Fakültesi01. Çankaya Üniversitesi2020-04-272025-09-182020-04-272025-09-182008Sever, 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).9780769531915https://doi.org/10.1109/BIOTECHNO.2008.23https://hdl.handle.net/20.500.12416/15026IARIAThe 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.eninfo:eu-repo/semantics/closedAccessConference Object10.1109/BIOTECHNO.2008.232-s2.0-52249124367