Evidence map›Paper›PMID 36966702›Full record

ReviewCurrent opinion in chemical biology2023

Recent advances in mass spectrometry-based computational metabolomics.

Timothy M D Ebbels, Justin J J van der Hooft, Haley Chatelaine, Corey Broeckling, Nicola Zamboni, Soha Hassoun, Ewy A Mathé

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Host metabolic responses to SARS-CoV-2 and influenza viruses: parallels and contrasts.Metabolomics : Official journal of the Metabolomic Society · 2026
    Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Metabolic engineering inaBIOTECH · 2025
    Review
  16. Article
  17. Article
  18. Advancing the Chemical Characterization ofPlants (Basel, Switzerland) · 2025
    Article
  19. Article
  20. Review
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

7 authors.

Timothy M D EbbelsSection of Bioinformatics, Department of Metabolism, Digestion & Reproduction, Imperial College London, Burlington Danes Building, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK. Electronic address: t.ebbels@imperial.ac.uk.
Justin J J van der HooftBioinformatics Group, Wageningen University & Research, Wageningen 6708 PB, the Netherlands; Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.
Haley ChatelaineInformatics Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, Rockville, MD, USA.
Corey BroecklingBioanalysis and Omics Center, Analytical Resources Core, Colorado State University, Fort Collins, CO, USA.
Nicola ZamboniInstitute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Soha HassounDepartment of Computer Science, Tufts University, Medford, MA, USA; Department of Chemical and Biological Engineering, Tufts University, Medford, MA, USA.
Ewy A MathéInformatics Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, Rockville, MD, USA. Electronic address: ewy.mathe@nih.gov.

Funding

Informatics Research CoreZICTR000410 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI MATHÉ, EWY · 2021 to 2025
$11.7M
Development of Informatics Capabilities for Tracking Unknown Mass Spectra in the National Metabolomics Data RepositoryU01CA235507 · NCI · UNIVERSITY OF NORTH CAROLINA CHARLOTTE · PI DU, XIUXIA · 2018 to 2021
$2.1M
Computational Techniques for Advancing Untargeted Metabolomics AnalysisR01GM132391 · NIGMS · TUFTS UNIVERSITY MEDFORD · PI HASSOUN, SOHA · 2019 to 2022
$1.5M
Deep Learning Models for Metabolomics AnalysisR35GM148219 · NIGMS · TUFTS UNIVERSITY MEDFORD · PI Soha Hassoun · 2023 to 2026
$1.4M
Informatics Research CoreZIATR000410 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI MATHE, EWY · 2020 to 2020
$595k
Intramural NIH HHS ZIA TR000410Intramural NIH HHS ZIC TR000410Medical Research Council MR/S019669/1NCI NIH HHS U01 CA235507NIGMS NIH HHS R01 GM132391NIGMS NIH HHS R35 GM148219
6 · The paper itself

Abstract

The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines. The field continues to expand as modern instrumentation produces datasets with increasing complexity, resolution, and sensitivity. These datasets must be processed, annotated, modeled, and interpreted to enable biological insight. Techniques for visualization, integration (within or between omics), and interpretation of metabolomics data have evolved along with innovation in the databases and knowledge resources required to aid understanding. In this review, we highlight recent advances in the field and reflect on opportunities and innovations in response to the most pressing challenges. This review was compiled from discussions from the 2022 Dagstuhl seminar entitled "Computational Metabolomics: From Spectra to Knowledge".

Indexed as

Computational BiologyMetabolomicsDatabases, FactualMass SpectrometryBenchmarkingCheminformaticsChemometricsMachine learningMetabolite identificationMetabolomicsMulti-omicsSmall moleculesVisualization

Identifiers

PMID36966702
PMCPMC11075003

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.