ArticlePLoS computational biology2021
Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 1 of them a synthesis that pooled it.
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Who cites it
126 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.Metabolomics : Official journal of the Metabolomic Society · 2023Pooled it
- Artificial Intelligence and Machine Learning in Mass Spectrometry-Based Proteomics and Metabolomics.Methods in molecular biology (Clifton, N.J.) · 2027Article
- 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
- Molecular Networking and Mass2Motif Analysis Prioritise Glycosylated Triterpenoid-Related Chemical Space in the Cytotoxic Fractions of EdibleFoods (Basel, Switzerland) · 2026Article
- DeepMASS v.2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites.Plant communications · 2026Article
- Single-Cell Insights into Medicinal Plant Development and Metabolism.Plants (Basel, Switzerland) · 2026Review
- Chemical Ontogeny in Plants: Developmental Dynamics of Specialized Metabolism and Implications for Ecology, Quality Control, and Bioprospecting.Plants (Basel, Switzerland) · 2026Review
- Machine Learning-Enhanced LC-HRMS Workflows for Suspect and Nontargeted Screening of Pesticide Residues in Fruits and Vegetables.Analytical chemistry · 2026Article
- PyCompound: An Open-Source Python Package for Spectral-Library Matching in Mass Spectrometry-Based Metabolomics.Metabolites · 2026Article
- Foundation Models for Liquid Chromatography-High-Resolution Mass Spectrometry: A New Era beyond Labeled Datasets.Analytical chemistry · 2026Article
- Article
- 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
- Benchmarking MS/MS Featurization Strategies for Machine Learning-Driven Metabolite Structure Annotation.Journal of the American Society for Mass Spectrometry · 2026Article
- Differentiation of disaccharide isomersThe Analyst · 2026Article
- Mass spectrometry-based metabolomics approaches to interrogate host-microbiome interactions in mammalian systems.Natural product reports · 2026Review
- Practical Workflow for Building Local Mass Spectral Libraries for Untargeted Metabolomics.Metabolites · 2026Article
- Generalist biological artificial intelligence in modeling the language of life.Nature biotechnology · 2026Review
- Why machine learning fails at mass spectrometry for small molecules.Nature metabolism · 2026Article
- Peak2Patch: High-Fidelity Functional Group Identification through Attention-Based Fusion of Infrared and Mass Spectra.ACS omega · 2026Article
66 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.
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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.