Evidence map›Paper›PMID 39305388›Full record

ReviewMetabolomics : Official journal of the Metabolomic Society2024

Navigating common pitfalls in metabolite identification and metabolomics bioinformatics.

Elva María Novoa-Del-Toro, Michael Witting

Abstract readReview
In one paragraph

Review in Metabolomics : Official journal of the Metabolomic Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Bridging bench and bedside: translational omics ofEuropean respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  2. Review
  3. Article
  4. Article
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  6. Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites.Journal of the American Society for Mass Spectrometry · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. PMconv: How to Compare Proteomes and Metabolomes?International journal of molecular sciences · 2026
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
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  18. Large-Scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  19. Article
  20. Article
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

2 authors.

Elva María Novoa-Del-ToroToxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP- Purpan, UPS, 180 chemin de Tournefeuille St-Martin-du-Touch, BP 3, Toulouse Cedex, 31931, France.ORCID http://orcid.org/0000-0002-6135-5839
Michael WittingMetabolomics and Proteomics Core, Helmholtz Zentrum München, 85764, Neuherberg, Germany. michael.witting@helmholtz-munich.de.ORCID http://orcid.org/0000-0002-1462-4426

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolomics, the systematic analysis of small molecules in a given biological system, emerged as a powerful tool for different research questions. Newer, better, and faster methods have increased the coverage of metabolites that can be detected and identified in a shorter amount of time, generating highly dense datasets. While technology for metabolomics is still advancing, another rapidly growing field is metabolomics data analysis including metabolite identification. Within the next years, there will be a high demand for bioinformaticians and data scientists capable of analyzing metabolomics data as well as chemists capable of using in-silico tools for metabolite identification. However, metabolomics is often not included in bioinformatics curricula, nor does analytical chemistry address the challenges associated with advanced in-silico tools. AIM OF REVIEW: In this educational review, we briefly summarize some key concepts and pitfalls we have encountered in a collaboration between a bioinformatician (originally not trained for metabolomics) and an analytical chemist. We identified that many misunderstandings arise from differences in knowledge about metabolite annotation and identification, and the proper use of bioinformatics approaches for these tasks. We hope that this article helps other bioinformaticians (as well as other scientists) entering the field of metabolomics bioinformatics, especially for metabolite identification, to quickly learn the necessary concepts for a successful collaboration with analytical chemists. KEY SCIENTIFIC CONCEPTS OF REVIEW: We summarize important concepts related to LC-MS/MS based non-targeted metabolomics and compare them with other data types bioinformaticians are potentially familiar with. Drawing these parallels will help foster the learning of key aspects of metabolomics.

Indexed as

Computational BiologyMetabolomicsHumansMetabolomeBioinformaticsData AnalysisLC-MS/MSMass SpectrometryMetabolite databasesMetabolite IdentificationMetabolomics

Identifiers

PMID39305388
PMCPMC11416380

What OpenQuestion holds

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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.