Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12570
Title: Truncation of protein sequences for fast profile alignment with application to subcellular localization
Authors: Mak, MW 
Wang, W
Kung, SY
Keywords: Cleavage sites prediction
Kernel discriminant analysis
Profiles alignment
Protein sequences
Subcellular localization
SVM
Issue Date: 2010
Source: Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, 2010, p. 115-120 How to cite?
Abstract: We have recently found that the computation time of homology-based subcellular localization can be substantially reduced by aligning profiles up to the cleavage site positions of signal peptides, mitochondrial targeting peptides, and chloroplast transit peptides [1]. While the method can reduce the profile alignment time by as much as 20 folds, it cannot reduce the computation time spent on creating the profiles. In this paper, we propose a new approach that can reduce both the profile creation time and profile alignment time. In the new approach, instead of cutting the profiles, we shorten the sequences by cutting them at the cleavage site locations. The shortened sequences are then presented to PSI-BLAST to compute the profiles. Experimental results and analysis of profile-alignment score matrices suggest that both profile creation time and profile alignment time can be reduced without sacrificing subcellular localization accuracy. Once a pairwise profile-alignment score matrix has been obtained, a one-vs-rest SVM classifier can be trained. To further reduce the training and recognition time of the classifier, we propose a perturbation discriminant analysis (PDA) technique. It was found that PDA enjoys a short training time as compared to the conventional SVM.
Description: 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, Hong Kong, 18-21 December 2010
URI: http://hdl.handle.net/10397/12570
ISBN: 9781424483075
DOI: 10.1109/BIBM.2010.5706548
Appears in Collections:Conference Paper

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