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Bayesian protein inference algorithmMSBayesPro is Bayesian protein inference algorithm for LC-MS/MS proteomics experiment. It is the proof-of-principle implementation of the Bayesian protein inference algorithm published in RECOMB 2008. It is available for the following platforms: Win32, Linux32bit, Linux64bit. And here are sample data1(detectability file, peptide identification), sample data2(detectability file, peptide identification), readme, and LICENSE for the program. Please read the readme and the reference paper before using the program. In case you want to test your own dataset, you will need to get the peptide detectability predictions (for all the peptides, IDENTIFIED or NOT, of the candidate proteins). You may want to check the peptide detectability predictor from here. An improved version of the algorithm is coming out soon...
Reference: Yong Fuga Li, Randy Arnold, Yixue Li, Predrag Radivojac, Quanhu Sheng and Haixu Tang. A Bayesian approach to protein inference problem in shotgun proteomics. J Comput Biol (2009) 16(8): 1-11. (PDF.) Yong Fuga Li, Randy Arnold, Yixue Li, Predrag Radivojac, Quanhu Sheng and Haixu Tang. A Bayesian approach to protein inference problem in shotgun proteomics. RECOMB 2008; & LNBI 4955, pp. 167 - 180, 2008 H. Tang, R. J. Arnold, P. Alves, Z. Xun, D. E. Clemmer, M. V. Novotny, J. P. Reilly and P. Radivojac, A computational approach toward label-free protein quantification using predicted peptide detectability. ISMB (Supplement of Bioinformatics) 2006: 481-488 |
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