Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/27635
Title: | Support vector machines with profile-based kernels for remote protein homology detection |
Authors: | Busuttil, Steven Abela, John Pace, Gordon J. |
Keywords: | Vector control Support vector machines |
Issue Date: | 2004 |
Publisher: | GIW |
Citation: | Busuttil, S., Abela, J., & Pace, G. J. (2004). Support vector machines with profile-based kernels for remote protein homology detection. The 15th International Conference on Genome Informatics (GIW'04). 191-200. |
Abstract: | Two new techniques for remote protein homology detection particulary suited for sparse data are introduced. These methods are based on position specific scoring matrices or profiles and use a support vector machine (SVM) for discrimination. The performance on standard benchmarks outperforms previous non-discriminative techniques and is comparable to that of other SVM-based methods while giving distinct advantages. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/27635 |
ISSN: | 09199454 |
Appears in Collections: | Scholarly Works - FacICTCS |
Files in This Item:
File | Description | Size | Format | |
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giw2004.pdf | 554.29 kB | Adobe PDF | View/Open |
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