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|Title:||A better gap penalty for Pairwise SVM||Authors:||Chua, H.N.
|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||URI:||http://scholarbank.nus.edu.sg/handle/10635/41501||ISBN:||1860944779||ISSN:||17516404|
|Appears in Collections:||Staff Publications|
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