Evidence map›Paper›PMID 24623587›Full record

ArticleMolecular & cellular proteomics : MCP2014

Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Umut H Toprak, Ludovic C Gillet, Alessio Maiolica, Pedro Navarro, Alexander Leitner, Ruedi Aebersold

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed
5.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 121 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. TOFNature communications · 2023
    Article
  19. Article
  20. Article

3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Umut H ToprakFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;
Ludovic C GilletFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;
Alessio MaiolicaFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;
Pedro NavarroFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;
Alexander LeitnerFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;
Ruedi AebersoldFrom the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland; §Faculty of Science, University of Zurich, Zurich, 8093 Zurich, Switzerland aebersold@imsb.biol.ethz.ch.
ETH Zurich · CHUniversity of Zurich · CH

Funding

European Research Council 233226
6 · The paper itself

Abstract

Quantifying the similarity of spectra is an important task in various areas of spectroscopy, for example, to identify a compound by comparing sample spectra to those of reference standards. In mass spectrometry based discovery proteomics, spectral comparisons are used to infer the amino acid sequence of peptides. In targeted proteomics by selected reaction monitoring (SRM) or SWATH MS, predetermined sets of fragment ion signals integrated over chromatographic time are used to identify target peptides in complex samples. In both cases, confidence in peptide identification is directly related to the quality of spectral matches. In this study, we used sets of simulated spectra of well-controlled dissimilarity to benchmark different spectral comparison measures and to develop a robust scoring scheme that quantifies the similarity of fragment ion spectra. We applied the normalized spectral contrast angle score to quantify the similarity of spectra to objectively assess fragment ion variability of tandem mass spectrometric datasets, to evaluate portability of peptide fragment ion spectra for targeted mass spectrometry across different types of mass spectrometers and to discriminate target assays from decoys in targeted proteomics. Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure. The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.

Indexed as

SoftwareAlgorithmsMass SpectrometryPeptidesProteomicsPeptides

Identifiers

PMID24623587
PMCPMC4125737
OpenAlexW2111115926

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.