De novo peptide sequencing via tandem mass spectrometry

peer-reviewed · Journal of Computational Biology · 1999

peer-reviewed · Journal of Computational Biology · 1999. Vlado Dancík et al. Peptide sequencing via tandem mass spectrometry (MS/MS) is one of the most powerful tools in proteomics for…

Date	1999-10-01
Type	peer-reviewed
Venue	Journal of Computational Biology
Publisher	Mary Ann Liebert
Contribution	algorithm
DOI	10.1089/106652799318300
Citations (OpenAlex)	598
Venue 2-year citedness	1.54

Abstract

Peptide sequencing via tandem mass spectrometry (MS/MS) is one of the most powerful tools in proteomics for identifying proteins. Because complete genome sequences are accumulating rapidly, the recent trend in interpretation of MS/MS spectra has been database search. However, de novo MS/MS spectral interpretation remains an open problem typically involving manual interpretation by expert mass spectrometrists. We have developed a new algorithm, SHERENGA, for de novo interpretation that automatically learns fragment ion types and intensity thresholds from a collection of test spectra generated from any type of mass spectrometer. The test data are used to construct optimal path scoring in the graph representations of MS/MS spectra. A ranked list of high scoring paths corresponds to potential peptide sequences. SHERENGA is most useful for interpreting sequences of peptides resulting from unknown proteins and for validating the results of database search algorithms in fully automated, high-throughput peptide sequencing.

Authors

Methods and tools

Sherenga: Graph-theoretic de novo (foundational)

Cites (7)

Cited by (186)

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