Evidence map›Paper›PMID 42254591›Full record

ArticleBioinformatics advances2026

eMZed 3: flexible and interactive development of scalable LC-MS/MS data analysis workflows in python.

Uwe Schmitt, Jethro Hemmann, Nicola Zamboni, Julia A Vorholt, Patrick Kiefer

Abstract read
In one paragraph

Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Uwe SchmittScientific IT Services, ETH Zurich, Binzmuehlestrasse 130, Zurich 8092, Switzerland.
Jethro HemmannJunior Research Group Metabolomics-Guided Natural Product Discovery, Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI), Beutenbergstraße 11a, Jena 07745, Germany.
Nicola ZamboniInstitute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, Zurich 8093, Switzerland.ORCID https://orcid.org/0000-0003-1271-1021
Julia A VorholtInstitute of Microbiology, ETH Zurich, Zurich, Vladimir-Prelog-Weg 4, Zurich 8093, Switzerland.
Patrick KieferInstitute of Microbiology, ETH Zurich, Zurich, Vladimir-Prelog-Weg 4, Zurich 8093, Switzerland.ORCID https://orcid.org/0000-0002-9159-0848

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary: Liquid chromatography-mass spectrometry (LC-MS/MS) data analysis requires adaptable software solutions to meet diverse analytical needs. We present eMZed 3, a modern Python framework for flexible and interactive analysis of LC-MS/MS data. eMZed 3 enables users to develop scalable workflows tailored to their specific requirements while leveraging Python's extensive ecosystem of libraries. Building on its predecessor, eMZed 3 is now Python 3-based and includes substantial enhancements, including support for chromatogram-based LC-MS data, a new SQLite-based backend supporting optional out-of-memory processing, and rich interactive visualization tools. Compared to the previous version, eMZed 3 is now split into three packages: Availability and implementation: eMZed 3 and its documentation are freely available at https://emzed.ethz.ch, the source code is hosted at https://gitlab.com/groups/emzed3.An online-executable example workflow is available on Binder at: https://mybinder.org/v2/gl/emzed3%2Femzed-example-workflow/HEAD?_labpath=example.ipynb.

Identifiers

PMID42254591
PMCPMC13242181

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.