Evidence map›Paper›PMID 39075613›Full record

ArticleJournal of cheminformatics2024

Reproducible MS/MS library cleaning pipeline in matchms.

Niek F de Jonge, Helge Hecht, Michael Strobel, Mingxun Wang, Justin J J van der Hooft, Florian Huber

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The MassBank contributions of the mFam collaboration.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

6 authors.

Niek F de JongeBioinformatics Group, Wageningen University & Research, 6708 PB, Wageningen, the Netherlands. niek.dejonge@wur.nl.
Helge HechtFaculty of Science, RECETOX, Masaryk University, Kotlářská 2, Brno, Czech Republic.
Michael StrobelDepartment of Computer Science and Engineering, University of California Riverside, 900 University Ave., Riverside, CA, 92521, USA.
Mingxun WangDepartment of Computer Science and Engineering, University of California Riverside, 900 University Ave., Riverside, CA, 92521, USA.
Justin J J van der HooftBioinformatics Group, Wageningen University & Research, 6708 PB, Wageningen, the Netherlands. justin.vanderhooft@wur.nl.
Florian HuberCentre for Digitalisation and Digitality, Düsseldorf University of Applied Sciences, 40476, Düsseldorf, Germany. florian.huber@hs-duesseldorf.de.

Funding

European Union's Horizon 2020 research and innovation programme 857560Research Infrastructure RECETOX RI LM2023069
6 · The paper itself

Abstract

Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.

Indexed as

Library cleaningMass spectrometryMetabolomicsMetadataPython Package

Identifiers

PMID39075613
PMCPMC11285329

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.