The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Improvements to the Percolator Algorithm for Peptide Identification from Shotgun Proteomics Data Sets
Open accessAbstract
Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the SEQUEST score function Xcorr fails to discriminate accurately between correct and incorrect peptide identifications. Several machine learning methods have been proposed to address the resulting classification task of distinguishing between correct and incorrect peptide-spectrum matches (PSMs). A recent example is Percolator, which uses semisupervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs identified by a database search algorithm. The current work describes three improvements to Percolator. (1) Percolator's heuristic optimization is replaced with a clear objective function, with intuitive reasons behind its choice. (2) Tractable nonlinear models are used instead of linear models, leading to improved accuracy over the original Percolator. (3) A method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value is proposed, which achieves further gains.
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Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Semi-supervised learning for peptide identification from shotgun proteomics datasets
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S., & MacCoss, M. J. (2007) · Nature Methods · doi:10.1038/nmeth1113 · Cited by 2,424
Self-citationAssigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases
Käll, L., Storey, J. D., MacCoss, M. J., & Noble, W. S. (2008) · Journal of Proteome Research · doi:10.1021/pr700600n · Cited by 607
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Hoffmann, M. A., Nothias, L.-F., Ludwig, M., Fleischauer, M., Gentry, E. C., Witting, M., Dorrestein, P. C., Dührkop, K., & Böcker, S. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01045-9 · Cited by 388
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Applications and challenges of forensic proteomics
Merkley, E. D., Wunschel, D. S., Wahl, K. L., & Jarman, K. H. (2019) · Forensic Science International · doi:10.1016/j.forsciint.2019.01.022 · Cited by 64
Multi cell line analysis of lysosomal proteomes reveals unique features and novel lysosomal proteins
Akter, F., Ponnaiyan, S., Kögler-Mohrbacher, B., Bleibaum, F., Damme, M., Renard, B. Y., & Winter, D. (2020) · doi:10.1101/2020.12.21.423747 · Cited by 55
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Autophagy-mediated metabolic effects of aspirin
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RTF2 controls replication repriming and ribonucleotide excision at the replisome
Conti, B. A., Ruiz, P. D., Broton, C., Blobel, N. J., Kottemann, M. C., Sridhar, S., Lach, F. P., Wiley, T. F., Sasi, N. K., Carroll, T., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45947-z · Cited by 8
Weiblen, C., Kits, K. D., Kleiner, M., Sauvageau, D., & Stein, L. Y. (2025) · mBio · doi:10.1128/mbio.01533-25 · Cited by 8
Metadata
- Authors
- Spivak, M., Weston, J., Bottou, L., Käll, L., & Noble, W. S.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-05-19
- Volume
- 8
- Issue
- 7
- Pages
- 3737-3745
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W1984450835
- Cited by
- 282
- References
- 4
- FWCI
- 3.52
- Type
- journal article
- Language
- en
- Open access
- green
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