Evidence map›Paper›PMID 36871033›Full record

ArticleJournal of cheminformatics2023

MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry.

Mahnoor Zulfiqar, Luiz Gadelha, Christoph Steinbeck, Maria Sorokina, Kristian Peters

Open access · goldAbstract read
In one paragraph

Article in Journal of cheminformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.2field-weighted citation impact, top 4% of its field
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

15 citing papers in PubMed, 34 citations in OpenAlex.

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  13. NanoLC-EI-MS: Perspectives in Biochemical Analysis.International journal of molecular sciences · 2023
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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

5 authors at 3 institutions in 1 country.

Mahnoor ZulfiqarInstitute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany. mahnoor.zulfiqar@uni-jena.de.
Luiz GadelhaInstitute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany.
Christoph SteinbeckInstitute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany. christoph.steinbeck@uni-jena.de.
Maria SorokinaInstitute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany.
Kristian PetersiDiv - German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, Leipzig, 04103, Germany. kristian.peters@ipb-halle.de.
Friedrich Schiller University Jena · DEBayer (Germany) · DEGerman Centre for Integrative Biodiversity Research · DE

Funding

Deutsche Forschungsgemeinschaft 239748522-SFB 1127Deutsche Forschungsgemeinschaft 390713860
6 · The paper itself

Abstract

Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS

Indexed as

FAIRMetabolite annotationTandem mass spectrometryUntargeted metabolomicsWorkflow

Identifiers

PMID36871033
PMCPMC9985203
OpenAlexW4323050593

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.