Skip Navigation



Bioinformatics Advance Access published online on June 20, 2006

Bioinformatics, doi:10.1093/bioinformatics/btl180
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrowOA All Versions of this Article:
22/14/1784    most recent
btl180v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Guo, J.
Right arrow Articles by Lin, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Guo, J.
Right arrow Articles by Lin, Y.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2006 The Author(s)
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

1 Laboratory of Statistical Computation & Bioinformatics, Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China

* To whom correspondence should be addressed.
Jian Guo, E-mail: guojian99{at}tsinghua.org.cn


   Abstract

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.


Associate Editor: Charlie Hodgman
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.