DocumentCode
1296566
Title
Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry
Author
Zhang, Jianqiu ; Zhou, Xiaobo ; Wang, Honghui ; Suffredini, Anthony ; Zhang, Lin ; Huang, Yufei ; Wong, Stephen
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA
Volume
58
Issue
11
fYear
2010
Firstpage
5883
Lastpage
5894
Abstract
In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000-15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert´s visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.
Keywords
Bayes methods; Markov processes; Monte Carlo methods; medical signal detection; molecular biophysics; patient diagnosis; proteins; time of flight mass spectra; time of flight mass spectroscopy; Bayesian peak detection algorithm; Markov chain Monte Carlo sampling; high resolution TOF mass spectrometry; high resolution time-of-flight mass spectrometry; parametric model; peptide ion peak detection; Bayesian methods; Chemicals; Detection algorithms; Instruments; Ions; Mass spectroscopy; Noise; Parametric statistics; Peptides; Permission; Protein engineering; Sampling methods; Signal resolution; Testing; Bayesian methods; Markov chain Monte Carlo; mass spectrometry; peptide peak detection; time-of-flight;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2010.2065226
Filename
5549940
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