Evidence map›Paper›PMID 23720762›Full record

ReviewMolecular & cellular proteomics : MCP2013

Combining results of multiple search engines in proteomics.

David Shteynberg, Alexey I Nesvizhskii, Robert L Moritz, Eric W Deutsch

Abstract readReview
In one paragraph

Review in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 1 pooled it
–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

85 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. SEMQuant: Extending Sipros-Ensemble with Match-Between-Runs for Comprehensive Quantitative Metaproteomics.Bioinformatics research and applications : ... international symposium, ISBRA ... proceedings. ISBRA (Conference) · 2024
    Article
  9. Bioinformatic Workflows for Metaproteomics.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Parasitology · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. The critical role that spectral libraries play in capturing the metabolomics community knowledge.Metabolomics : Official journal of the Metabolomic Society · 2022
    Review
  18. Review
  19. Proteomic Comparison of Ivermectin Sensitive and ResistantAntibiotics (Basel, Switzerland) · 2022
    Article
  20. Article

25 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

4 authors.

David ShteynbergInstitute for Systems Biology, Seattle, Washington 98109, USA.
Alexey I Nesvizhskii
Robert L Moritz
Eric W Deutsch

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
Complete Human Peptide- and MRM-AtlasRC2HG005805 · NHGRI · INSTITUTE FOR SYSTEMS BIOLOGY · PI HOOD, LEROY E, MORITZ, ROBERT L · 2009 to 2010
$4.6M
Analysis and Statistical Validation of Proteomic DatasetsR01CA126239 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NESVIZHSKII, ALEXEY I · 2006 to 2009
$1.2M
NCI NIH HHS R01 CA126239NCI NIH HHS R01-CA-126239NHGRI NIH HHS R01 HG005805NHGRI NIH HHS RC2 HG005805NIGMS NIH HHS 2P50 GM076547NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221NIGMS NIH HHS R01 GM094231NIGMS NIH HHS R01-GM-094231
6 · The paper itself

Abstract

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Indexed as

Search EngineAmino Acid SequenceAnimalsHumansPeptidesProteomicsROC CurveSoftwarePeptides

Identifiers

PMID23720762
PMCPMC3769318

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.