Bioinformatics Advance Access published online on June 20, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl180
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1 Laboratory of Statistical Computation & Bioinformatics, Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China
* To whom correspondence should be addressed.
Summary: This paper introduces a new subcellular localization system (TSSub) for eukaryotic proteins. This system extracts features from both profiles and amino acid sequences. Four different features are extracted from profiles by four probabilistic neural network (PNN) classifiers respectively (the amino acid composition from whole profiles; the amino acid composition from the N-terminus of profiles; the dipeptide composition from whole profiles and the amino aicd composition from fragments of profiles). In addition, a support vector machine (SVM) classifier is added to implement the residue-couple feature extracted from amino acid sequences. The results from the five classifiers are fused by an additional SVM classifier. The overall accuracies of this TSSub reach 93.0% and 77.4% on Reinhardt and Hubbard's eukaryotic protein dataset and Huang and Li's eukaryotic protein dataset, respectively. The comparison with existing methods results shows TSSub provides better prediction performance than existing methods. Availability: The web server is available from http://166.111.24.5/webtools/TSSub/index.html. Supplementary Note: The supplementary note can be downloaded from http://166.111.24.5/webtools/TSSub/Supplementary.htm.
Received July 11, 2005
Revised April 4, 2006
Accepted May 4, 2006
Applications note
TSSub: eukaryotic protein subcellular localization by extracting features from profiles
Jian Guo 1 *
and
Yuanlie Lin 1
Jian Guo, E-mail: guojian99{at}tsinghua.org.cn
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Abstract
Associate Editor: Charlie Hodgman
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