ReviewNature protocols2024
Reproducible mass spectrometry data processing and compound annotation in MZmine 3.
Review in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
What it found
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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.
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.
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Who cites it
74 citing papers in PubMed.
- Lipidomic profiling of PEX11β knockout T-REx 293 cells reveals lipid shifts suggesting potential metabolic perturbations.Biochemistry and biophysics reports · 2026Article
- eCOMET: an R package for evaluating metabolic diversity and enrichment from LC-MS/MS data to test ecological hypotheses from individuals to ecosystems.The New phytologist · 2026Article
- Computational metabolomics at scale: from open data to insight.Current opinion in biotechnology · 2026Review
- Monounsaturated fatty acid biosynthesis is critical for streptococcal envelope homeostasis and stress tolerance.Journal of bacteriology · 2026Article
- Environmental Contaminants in Surface Snow Samples Made from Reclaimed Water at a Ski Resort: A Mass Spectrometry Analysis.ACS environmental Au · 2026Article
- MetaboAnnotate: An AI-powered Multiagent Framework for Integrating Annotation Tools for Untargeted Metabolomics.Analytical chemistry · 2026Article
- Mass Spectrometry-Based Chromatographic and Computational Workflows for Biomarker and Therapeutic Target Discovery: A Comprehensive Review.Biomedical chromatography : BMC · 2026Review
- Navigating the glycomics landscape with CE-MS: advances in sample preparation and analytical strategies.The Analyst · 2026Review
- Integrated strategy for multivariate quality description ofFood chemistry: X · 2026Article
- Divergent skeletal muscle metabolite exchange in insulin-like growth factor-1-stimulated myotubes and resistance-exercised human muscle.Experimental physiology · 2026Article
- LC-HRMS and Molecular Networking for Non-Targeted Screening of Emerging Contaminants in Cosmetics: Workflow, Applications, and Regulatory Challenges.Molecules (Basel, Switzerland) · 2026Review
- Comprehensive Liquid Chromatography-Mass Spectrometry-based Metabolite Annotation Elucidates the Chemical Diversity of an Endangered Plant Nardostachys jatamansi.Journal of separation science · 2026Article
- MALDI Tandem Mass Spectrometry for Colony-Based Dereplication of Natural Products.bioRxiv : the preprint server for biology · 2026Article
- Rapid Classification of Coffee Varieties Using Single-Bean Hot Gas Extraction Ion-Mobility Spectrometry with Machine Learning.ACS measurement science au · 2026Article
- Exploring Acylcarnitine Metabolism Using Reverse Metabolomics.Analytical chemistry · 2026Article
- Comprehensive Metabolite Profile and Cytotoxic Constituents ofJournal of natural products · 2026Article
- Structural determination of natural products at speeds and scale of high-throughput screening.Natural product reports · 2026Review
- Clinical Significance of Plasma Sphingosine-1-Phosphate Decline in Progression of Spinal and Bulbar Muscular Atrophy.Journal of clinical neurology (Seoul, Korea) · 2026Article
- Decoding cancer across scales with metabolomics.Nature reviews. Cancer · 2026Review
- Genome Mining Guided Identification of the Metallophore Delftichelin A fromJournal of natural products · 2026Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.
Indexed as
Identifiers
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Registered trials
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.