Bioinformatics Advance Access originally published online on November 10, 2008
Bioinformatics 2009 25(1):123-125; doi:10.1093/bioinformatics/btn576
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Prediction of translation initiation site for microbial genomes with TriTISA
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
This article has been cited by other articles:
![]() |
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] |
||||
