Evidence map›Paper›PMID 28436590›Full record

ReviewMass spectrometry reviews2018

Identification of small molecules using accurate mass MS/MS search.

Tobias Kind, Hiroshi Tsugawa, Tomas Cajka, Yan Ma, Zijuan Lai, Sajjan S Mehta, Gert Wohlgemuth, Dinesh Kumar Barupal, Megan R Showalter, Masanori Arita and 1 more

Abstract readReview
In one paragraph

Review in Mass spectrometry reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 198 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
198citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. The MassBank contributions of the mFam collaboration.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Secondary metabolism ofApplied and environmental microbiology · 2026
    Review
  16. Article
  17. Large-Scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  18. Review
  19. Article
  20. Automated metabolite formula ranking using formula subset analysis for LC-MS/MS-based metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2025
    Article

138 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

11 authors.

Tobias KindGenome Center, Metabolomics, UC Davis, Davis, California.
Hiroshi TsugawaRIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa, Japan.
Tomas CajkaGenome Center, Metabolomics, UC Davis, Davis, California.
Yan MaNational Institute of Biological Sciences, Beijing, People's Republic of China.
Zijuan LaiGenome Center, Metabolomics, UC Davis, Davis, California.
Sajjan S MehtaGenome Center, Metabolomics, UC Davis, Davis, California.
Gert WohlgemuthGenome Center, Metabolomics, UC Davis, Davis, California.
Dinesh Kumar BarupalGenome Center, Metabolomics, UC Davis, Davis, California.
Megan R ShowalterGenome Center, Metabolomics, UC Davis, Davis, California.
Masanori AritaRIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa, Japan.
Oliver FiehnGenome Center, Metabolomics, UC Davis, Davis, California.

Funding

West Coast Central Comprehensive Metabolomics Resource Core (WC3MRC)U24DK097154 · NIDDK · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FIEHN, OLIVER · 2012 to 2017
$9.9M
Genomewide Association Study of Lipid Response to Fenofibrate and Dietary FatR01HL091357 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2008 to 2018
$5.8M
NHLBI NIH HHS R01 HL091357NIDDK NIH HHS U24 DK097154
6 · The paper itself

Abstract

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS

Indexed as

Machine LearningSoftwareComputer SimulationDatabases, ChemicalHumansInformation DisseminationModels, ChemicalQuantum TheorySmall Molecule LibrariesTandem Mass SpectrometrySmall Molecule Librariescompound identificationhigh-resolution mass spectrometrylibrary searchtandem mass spectrometry

Identifiers

PMID28436590
PMCPMC8106966

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.