Evidence map›Paper›PMID 21572408›Full record

ArticleNature methods2011

Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra.

Ari M Frank, Matthew E Monroe, Anuj R Shah, Jeremy J Carver, Nuno Bandeira, Ronald J Moore, Gordon A Anderson, Richard D Smith, Pavel A Pevzner

Abstract read
In one paragraph

Article in Nature methods, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
–field-weighted citation impact
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

54 citing papers in PubMed.

  1. Article
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  4. MS/MS Mass Spectrometry Filtering Tree for Bile Acid Isomer Annotation.bioRxiv : the preprint server for biology · 2025
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  6. The microbiome diversifiesbioRxiv : the preprint server for biology · 2024
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  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Wood Degradation byJournal of fungi (Basel, Switzerland) · 2023
    Article
  14. Article
  15. The critical role that spectral libraries play in capturing the metabolomics community knowledge.Metabolomics : Official journal of the Metabolomic Society · 2022
    Review
  16. Article
  17. Article
  18. Article
  19. Optimization of LC-MSMetabolites · 2022
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Ari M FrankDepartment of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA.
Matthew E Monroe
Anuj R Shah
Jeremy J Carver
Nuno Bandeira
Ronald J Moore
Gordon A Anderson
Richard D Smith
Pavel A Pevzner

Funding

WORKSHOP AND TRAINING ACTIVITIESP41RR018522 · NCRR · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2003 to 2011
$25.1M
CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
NCRR NIH HHS 1-P41-RR024851NCRR NIH HHS P41 RR018522NCRR NIH HHS P41 RR024851NCRR NIH HHS RR18522
6 · The paper itself

Abstract

Tandem mass spectrometry (MS/MS) experiments yield multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra they generate. We propose a spectral archives approach that clusters MS/MS datasets, representing similar spectra by a single consensus spectrum. Spectral archives extend spectral libraries by analyzing both identified and unidentified spectra in the same way and maintaining information about peptide spectra that are common across species and conditions. Thus archives offer both traditional library spectrum similarity-based search capabilities along with new ways to analyze the data. By developing a clustering tool, MS-Cluster, we generated a spectral archive from ∼1.18 billion spectra that greatly exceeds the size of existing spectral repositories. We advocate that publicly available data should be organized into spectral archives rather than be analyzed as disparate datasets, as is mostly the case today.

Indexed as

Databases, FactualArchivesPeptidesProteinsProteomicsTandem Mass SpectrometryPeptidesProteins

Identifiers

PMID21572408
PMCPMC3128193

What OpenQuestion holds

Textmetadata
LicenceTDM
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.