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Cited by 261

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Experimental Protein Mixture for Validating Tandem Mass Spectral Analysis

Keller, Andrew, Purvine, Samuel, Nesvizhskii, Alexey I., Stolyar, Sergey, Goodlett, David R., Kolker, Eugene·2002·OMICS: A Journal of Integrative Biology

Abstract

Several methods have been used to identify peptides that correspond to tandem mass spectra. In this work, we describe a data set of low energy tandem mass spectra generated from a control mixture of known protein components that can be used to evaluate the accuracy of these methods. As an example, these spectra were searched by the SEQUEST application against a human peptide sequence database. The numbers of resulting correct and incorrect peptide assignments were then determined. We show how the sensitivity and error rate are affected by the use of various filtering criteria based upon SEQUEST scores and the number of tryptic termini of assigned peptides.

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Metadata

Authors
Keller, A., Purvine, S., Nesvizhskii, A. I., Stolyar, S., Goodlett, D. R., & Kolker, E.
Venue
OMICS: A Journal of Integrative Biology
Published
2002-04
Volume
6
Issue
2
Pages
207-212
ISSN
  • 1536-2310 (ISSN-L)
  • 1557-8100
OpenAlex
W1543113652
Cited by
261
References
0
FWCI
11.07
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Experimental Protein Mixture for Validating Tandem Mass Spectral Analysis. https://app.cochat.ai/papers/10.1089/153623102760092805
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Keller, A., Purvine, S., Nesvizhskii, A. I., Stolyar, S., Goodlett, D. R., & Kolker, E. (2002). Experimental Protein Mixture for Validating Tandem Mass Spectral Analysis. OMICS: A Journal of Integrative Biology. https://doi.org/10.1089/153623102760092805

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.