ArticleNature communications2023
Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 73 citations in OpenAlex.
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- Enhancing Molecular Change: Iron-Mediated Photochemistry Increases DOM Transformation in Tropical Peatland Canals.Environmental science & technology · 2026Article
- Ordering molecular diversity in untargeted metabolomics via molecular community networking.Cell reports methods · 2026Article
- Large-scale discovery and annotation of substructure patterns in mass spectrometry profiles.Nature communications · 2026Article
- Structure-informed deep generation enables de novo metabolite annotation in untargeted metabolomics.Nature communications · 2026Article
- Mapping the mammalian dark metabolome bybioRxiv : the preprint server for biology · 2026Article
- Self-supervised learning of molecular representations from millions of tandem mass spectra using DreaMS.Nature biotechnology · 2026Article
- Paenidepsins are a Family of Lipopeptides fromJournal of natural products · 2026Article
- Integrating Metabolomics and Proteomics to Reveal the Regulatory Network Governing the Natural Variation in Rice Seed Germination Rate.Plants (Basel, Switzerland) · 2026Article
- The undiscovered natural product potential of Actinomycetes.The Journal of antibiotics · 2026Article
- Review
- A resource to empirically establish drug exposure records directly from untargeted metabolomics data.Nature communications · 2025Article
- Molecules to medicine: advances in metabolomics for natural product drug discovery.Current opinion in biotechnology · 2025Review
- A large language model for deriving spectral embeddings for accurate compound identification in mass spectrometry.Communications chemistry · 2025Article
- Optimization of the Extraction of Bioactive Compounds and Metabolomic Profile ofPlants (Basel, Switzerland) · 2025Article
- Article
- Urinary Metabolomic Profile is Minimally Impacted by Common Storage Conditions and Additives.International urogynecology journal · 2025Article
- Structural annotation of full-scan MS data: A unified solution for LC-MS and MS imaging analyses.bioRxiv : the preprint server for biology · 2025Article
- SimMS: a GPU-accelerated cosine similarity implementation for tandem mass spectrometry.Bioinformatics (Oxford, England) · 2025Article
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Authors and funding
32 authors at 15 institutions in 12 countries.
Funding
Abstract
Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.
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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.