ReviewAnalytical chemistry2025
Introducing "Identification Probability" for Automated and Transferable Assessment of Metabolite Identification Confidence in Metabolomics and Related Studies.
Review in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Machine Learning-Enhanced LC-HRMS Workflows for Suspect and Nontargeted Screening of Pesticide Residues in Fruits and Vegetables.Analytical chemistry · 2026Article
- Unravelling the phytochemical complexity of neuroprotective plants: a metabolomics approach to Alzheimer's disease.Molecular biology reports · 2026Review
- Metabolite Fraction Libraries for Quantitative NMR Metabolomics.Analytical chemistry · 2026Article
- A lipidomics roadmap: from basic research to societal challenges.Nature communications · 2026Review
- Assessing the metabolomics "dark matter" by a detectable khipu model.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Decoding cancer across scales with metabolomics.Nature reviews. Cancer · 2026Review
- Implementing Annotation Confidence Scoring in Untargeted Mass Spectrometry Workflows for Small Molecule Analysis.Analytical chemistry · 2026Article
- Evaluation of MassFrontier, MetFrag, MS-FINDER, and SIRIUS for Metabolite Annotation Using an Experimental LC-HRMS Dataset.Biomedicines · 2026Article
- Practicing Data Science in Interactive Notebooks.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Metabolite Fraction Libraries for Quantitative NMR Metabolomics.bioRxiv : the preprint server for biology · 2025Article
- MetScribeR: A Semiautomated Tool for Data Processing of In-House LC-MS Metabolite Reference Libraries.Journal of proteome research · 2025Article
- Updated Guidance for Communicating PFAS Identification Confidence with Ion Mobility Spectrometry.Environmental science & technology · 2025Article
- Machine Learning for Enhanced Identification Probability in RPLC/HRMS Nontargeted Workflows.Analytical chemistry · 2025Article
- Do experimental projection methods outcompete retention time prediction models in non-target screening? A case study on LC/HRMS interlaboratory comparison data.The Analyst · 2025Article
- Assessing the Impact of Measurement Precision on Metabolite Identification Probability in Multidimensional Mass Spectrometry-Based, Reference-Free Metabolomics.Analytical chemistry · 2025Article
- Constructing a consensus serum metabolome.bioRxiv : the preprint server for biology · 2025Article
- Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer.Nature methods · 2025Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence─the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in the context of the chemical space being considered. Neither are they easily automated nor transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/
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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.