Journal Article

Prediction of translation initiation site for microbial genomes with TriTISA

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

in Bioinformatics

Volume 25, issue 1, pages 123-125
Published in print January 2009 | ISSN: 1367-4803
Published online November 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn576
Prediction of translation initiation site for microbial genomes with TriTISA

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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@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.

Journal Article.  1723 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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