A Statistical Model for Identifying Proteins by Tandem Mass Spectrometry
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Abstract
A statistical model is presented for computing probabilities that proteins are present in a sample on the basis of peptides assigned to tandem mass (MS/MS) spectra acquired from a proteolytic digest of the sample. Peptides that correspond to more than a single protein in the sequence database are apportioned among all corresponding proteins, and a minimal protein list sufficient to account for the observed peptide assignments is derived using the expectation-maximization algorithm. Using peptide assignments to spectra generated from a sample of 18 purified proteins, as well as complex H. influenzae and Halobacterium samples, the model is shown to produce probabilities that are accurate and have high power to…
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4Topics & keywords
Topics
Keywords
- Chemistry
- Bottom-up proteomics
- Tandem mass spectrometry
- Mass spectrometry
- Proteomics
- Protein sequencing
- Peptide
- Peptide mass fingerprinting
UN Sustainable Development Goals
- Reduced inequalities
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