A graph-convolutional neural network model for the prediction of chemical reactivity

We present a supervised learning approach to predict the products of organic reactions given their reactants, reagents, and solvent(s). The prediction task is factored into two stages comparable to manual expert approaches: considering possible sites of reactivity and evaluating their relative likel...

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Detalles Bibliográficos
Autores principales: Coley, Connor W., Jin, Wengong, Rogers, Luke, Jamison, Timothy F., Jaakkola, Tommi S., Green, William H., Barzilay, Regina, Jensen, Klavs F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2018
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335848/
https://www.ncbi.nlm.nih.gov/pubmed/30746086
http://dx.doi.org/10.1039/c8sc04228d

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335848/
https://www.ncbi.nlm.nih.gov/pubmed/30746086
http://dx.doi.org/10.1039/c8sc04228d

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