Rapid prediction of NMR spectral properties with quantified uncertainty
Abstract Accurate calculation of specific spectral properties for NMR is an important step for molecular structure elucidation. Here we report the development of a novel machine learning technique for accurately predicting chemical shifts of both $${^1\mathrm{H}}$$ 1H and $${^{13}\mathrm{C}}$$ 13C...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-08-01
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| Series: | Journal of Cheminformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13321-019-0374-3 |