Skip Navigation


Bioinformatics Advance Access originally published online on November 10, 2008
Bioinformatics 2009 25(1):123-125; doi:10.1093/bioinformatics/btn576
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
25/1/123    most recent
btn576v1
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
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Hu, G.-Q.
Right arrow Articles by She, Z.-S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Hu, G.-Q.
Right arrow Articles by She, Z.-S.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Prediction of translation initiation site for microbial genomes with TriTISA

Gang-Qing Hu 1,2, Xiaobin Zheng 1,2, Huai-Qiu Zhu 1,2 and Zhen-Su She 1,2,*

1State Key Lab for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and 2Center for Theoretical Biology, Peking University, Beijing 100871, China

*To whom correspondence should be addressed.


   Abstract

Summary: We report a new and simple method, TriTISA, for accurate prediction of translation initiation site (TIS) of microbial genomes. TriTISA classifies all candidate TISs into three categories based on evolutionary properties, and characterizes them in terms of Markov models. Then, it employs a Bayesian methodology for the selection of true TIS with a non-supervised, iterative procedure. Assessment on experimentally verified TIS data shows that TriTISA is overall better than all other methods of the state-of-the-art for microbial genome TIS prediction. In particular, TriTISA is shown to have a robust accuracy independent of the quality of initial annotation.

Availability: The C++ source code is freely available under the GNU GPL license via http://mech.ctb.pku.edu.cn/protisa/TriTISA.

Contact: she{at}pku.edu.cn

Supplementary information: Full documentation of the program, containing installation instructions and other operational details, is available on our website. Supplementary data are available at Bioinformatics online.

Associate Editor: Limsoon Wong


Received on May 21, 2008; revised on November 4, 2008; accepted on November 4, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
BioinformaticsHome page
G.-Q. Hu, J.-T. Guo, Y.-C. Liu, and H. Zhu
MetaTISA: Metagenomic Translation Initiation Site Annotator for improving gene start prediction
Bioinformatics, July 15, 2009; 25(14): 1843 - 1845.
[Abstract] [Full Text] [PDF]



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.