A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes.

By D. Fenyö, Ronald C. Beavis. Analytical Chemistry, 2003

486 citations recorded by the source corpus.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/3d744cf9d758aa51e47a946af4447daf26cec1d6

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Citations in the corpus

SearchGUI: An open‐source graphical user interface for simultaneous OMSSA and X!Tandem searches (2011, methodology): “Several algorithms, both free and commercial, have been developed for this purpose, including MASCOT [2], SEQUEST [3], OMSSA (open mass spectrometry search algorithm) [4], VEMS [5] and X!Tandem [6].”
Analysis and validation of proteomic data generated by tandem mass spectrometry (2007, background): “, or by empirical fitting of the observed distribution of score”
Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations (2005, methodology): “Furthermore, Mascot suggests a 'homology' scoring threshold that is similar to a described measurement that uses the distribution of scores returned for peptides matching the observed precursor mas”
Spectral Probabilities and Generating Functions of Tandem Mass Spectra: a Strike Against Decoy Databases (2008, methodology): “While the approaches [5,6,7,16] are very valuable, neither of them rigorously solves the Spectral Matching Problem for individual spectra: instead they compute the error rates based on approximate fitting the empirical distributions to a standard distribution that may not carefully reflect the speci”
Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra (2004, background): “There is evidence that the identification process is not significantly affected by the reduced mass accuracy even though a larger number of peptides are considered in the searc”
A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics (2010, background): “[162] Fenyo D, Beavis RC.”
iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates* (2011, methodology): “Tandem, and OMSSA, convert the original search scores into expectation values ( E -values (43)) and report them as confidence scores for individual PSMs.”