ArticleACS central science2024
Accurate and Efficient Structure Elucidation from Routine One-Dimensional NMR Spectra Using Multitask Machine Learning.
Article in ACS central science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Predicting molecular structure from sparse NMR data, proof-of-concept using a graph neural network.Digital discovery · 2026Article
- Computational data as the fuel for AI in chemistry.Chemical science · 2026Review
- Vib2Mol: from vibrational spectra to molecular structures-a unified deep learning framework.Chemical science · 2026Article
- MolDeTr: A Chemistry-Informed Deep Learning Model for Next-Generation Automated Analysis of 1H NMR Spectra.Analytical chemistry · 2026Article
- Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.Chemical reviews · 2026Review
- End-to-end molecular structure elucidation from multimodal NMR spectra images using vision transformers.Chemical science · 2026Article
- End-to-end multimodal structure elucidation from raw spectra combining contrastive learning and evolutionary algorithms.Nature communications · 2026Article
- Generalist biological artificial intelligence in modeling the language of life.Nature biotechnology · 2026Review
- Unraveling the coordination isomerism by ligand hyperfine NMR shifts.Chemical science · 2026Article
- A Multimodal Representation Learning Framework for Molecular Graph and NMR Spectrum Alignment.Entropy (Basel, Switzerland) · 2026Article
- NMR-Solver: automated structure elucidation via large-scale spectral matching and physics-guided fragment optimization.Nature communications · 2026Article
- SPECTRE: A Multimodal Spectral Transformer for Small Molecule Annotation.Journal of chemical information and modeling · 2026Article
- Assessing the Chemical Intelligence of Large Language Models.Journal of chemical information and modeling · 2026Article
- Advancing Structure Elucidation with a Flexible Multi-Spectral AI Model.Angewandte Chemie (International ed. in English) · 2026Article
- Machine learning spectroscopy to advance computation and analysis.Chemical science · 2025Review
- Towards automatically verifying chemical structures: the powerful combination ofChemical science · 2025Article
- Exploring the Frontiers of Computational NMR: Methods, Applications, and Challenges.Chemical reviews · 2025Review
- Setting new benchmarks in AI-driven infrared structure elucidation.Digital discovery · 2025Article
- Accurate and Efficient Structure Elucidation from Routine One-Dimensional NMR Spectra Using Multitask Machine Learning.ACS central science · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rapid determination of molecular structures can greatly accelerate workflows across many chemical disciplines. However, elucidating structure using only one-dimensional (1D) NMR spectra, the most readily accessible data, remains an extremely challenging problem because of the combinatorial explosion of the number of possible molecules as the number of constituent atoms is increased. Here, we introduce a multitask machine learning framework that predicts the molecular structure (formula and connectivity) of an unknown compound solely based on its 1D
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Registered trials
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