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...

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Detalles Bibliográficos
Autores principales: Guan, Yanfei, Coley, Connor W., Wu, Haoyang, Ranasinghe, Duminda, Heid, Esther, Struble, Thomas J., Pattanaik, Lagnajit, Green, William H., Jensen, Klavs F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2020
Materias:
Chemistry
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8179287/
https://www.ncbi.nlm.nih.gov/pubmed/34163985
http://dx.doi.org/10.1039/d0sc04823b

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