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Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors
Accurate and rapid evaluation of whether substrates can undergo the desired the transformation is crucial and challenging for both human knowledge and computer predictions. Despite the potential of machine learning in predicting chemical reactivity such as selectivity, popular feature engineering an...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society of Chemistry
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8179287/ https://www.ncbi.nlm.nih.gov/pubmed/34163985 http://dx.doi.org/10.1039/d0sc04823b |