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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Man-Wai Mak Wei Wang Sun-Yuan Kung |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Electrical Engineering, Princeton University, New Jersey, USA (Sun-Yuan Kung) || Dept. of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR (Man-Wai Mak; Wei Wang) |
| 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 chloro-plast 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. |
| Starting Page | 115 |
| Ending Page | 120 |
| File Size | 494488 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424483068 |
| e-ISBN | 9781424483075 |
| DOI | 10.1109/BIBM.2010.5706548 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | kernel discriminant analysis Amino acids SVM profiles alignment Training Proteins Support vector machines Accuracy Subcellular localization cleavage sites prediction Kernel Personal digital assistants protein sequences |
| Content Type | Text |
| Resource Type | Article |
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