ArticleBriefings in bioinformatics2025
SingleFrag: a deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Benchmarking MS/MS Featurization Strategies for Machine Learning-Driven Metabolite Structure Annotation.Journal of the American Society for Mass Spectrometry · 2026Article
- Combating Antibacterial Resistance: The Integrative Role of Artificial Intelligence in Bio-Based Product Development.Antibiotics (Basel, Switzerland) · 2026Review
- Evaluation of MassFrontier, MetFrag, MS-FINDER, and SIRIUS for Metabolite Annotation Using an Experimental LC-HRMS Dataset.Biomedicines · 2026Article
- Automated metabolite formula ranking using formula subset analysis for LC-MS/MS-based metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Large-scale generation of in silico based spectral libraries to annotate dark chemical space features in non-target analysis.Analytical and bioanalytical chemistry · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
Metabolite and small molecule identification via tandem mass spectrometry (MS/MS) involves matching experimental spectra with prerecorded spectra of known compounds. This process is hindered by the current lack of comprehensive reference spectral libraries. To address this gap, we need accurate in silico fragmentation tools for predicting MS/MS spectra of compounds for which empirical spectra do not exist. Here, we present SingleFrag, a novel deep learning tool that predicts individual fragments separately, rather than attempting to predict the entire fragmentation spectrum at once. Our results demonstrate that SingleFrag surpasses state-of-the-art in silico fragmentation tools, providing a powerful method for annotating unknown MS/MS spectra of known compounds. As a proof of concept, we successfully annotate three previously unidentified compounds frequently found in human samples.
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