Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 504

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A method for reducing the time required to match protein sequences with tandem mass spectra

Craig, Robertson, Beavis, Ronald C.·2003·Rapid Communications in Mass Spectrometry

Abstract

An algorithm for reducing the time necessary to match a large set of peptide tandem mass spectra with a list of protein sequences is described. This algorithm breaks the process into multiple steps. A rapid survey step identifies all protein sequences that are reasonable candidates for a match with a set of tandem mass spectra. These candidates are then used as models, which are refined by detailed analysis of the set of tandem mass spectra for evidence of incomplete enzymatic hydrolysis, non‐specific hydrolysis and chemical modifications of amino acid residues resulting from either post‐translational modifications or sample handling. Compared with current one‐step methods for matching proteins to mass spectra, this multiple‐step method can decrease the time required for the calculation by several orders of magnitude. Copyright © 2003 John Wiley & Sons, Ltd.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/rcm.1198

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 504

Metadata

Authors
Craig, R., & Beavis, R. C.
Venue
Rapid Communications in Mass Spectrometry
Publisher
Wiley
Published
2003-09-19
Volume
17
Issue
20
Pages
2310-2316
ISSN
  • 0951-4198 (ISSN-L)
  • 1097-0231
OpenAlex
W2163078532
Cited by
504
References
1
FWCI
8.18
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A method for reducing the time required to match protein sequences with tandem mass spectra. https://app.cochat.ai/papers/10.1002/rcm.1198
The paper
Craig, R., & Beavis, R. C. (2003). A method for reducing the time required to match protein sequences with tandem mass spectra. Rapid Communications in Mass Spectrometry. https://doi.org/10.1002/rcm.1198

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.