期刊
NATURE METHODS
卷 8, 期 5, 页码 430-U85出版社
NATURE PORTFOLIO
DOI: 10.1038/NMETH.1584
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资金
- Forschungskredit of the University of Zurich
- University of Zurich
- GEBERT-RUF Stiftung and Swiss National Science Foundation [31000-10767]
- US National Heart, Lung, and Blood Institute
- US National Institutes of Health [N01-HV-28179]
- SystemsX.ch, the Swiss initiative for systems biology
S elected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.
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