A Data Fusion Approach In Protein Homology Detection
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Date
2008
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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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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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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
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7
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12