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Title: A better gap penalty for Pairwise SVM
Authors: Chua, H.N.
Sung, W.-K. 
Issue Date: 2005
Citation: Chua, H.N.,Sung, W.-K. (2005). A better gap penalty for Pairwise SVM. Series on Advances in Bioinformatics and Computational Biology 1 : 11-20. ScholarBank@NUS Repository.
Abstract: SVM-Pairwise was a major breakthrough in remote homology detection techniques, significantly outperforming previous approaches. This approach has been extensively evaluated and cited by later works, and is frequently taken as a benchmark. No known work however, has examined the gap penalty model employed by SVM-Pairwise. In this paper, we study in depth the relevance and effectiveness of SVM-Pairwise's gap penalty model with respect to the homology detection task. We have identified some limitations in this model that prevented the SVM-Pairwise algorithm from realizing its full potential and also studied several ways to overcome them. We discovered a more appropriate gap penalty model that significantly improves the performance of SVM-Pairwise.
Source Title: Series on Advances in Bioinformatics and Computational Biology
ISBN: 1860944779
ISSN: 17516404
Appears in Collections:Staff Publications

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