Please use this identifier to cite or link to this item:
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

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on May 22, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.