Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

[Image: see text] We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which...

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Detalles Bibliográficos
Autores principales: Liu, Bowen, Ramsundar, Bharath, Kawthekar, Prasad, Shi, Jade, Gomes, Joseph, Luu Nguyen, Quang, Ho, Stephen, Sloane, Jack, Wender, Paul, Pande, Vijay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2017
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658761/
https://www.ncbi.nlm.nih.gov/pubmed/29104927
http://dx.doi.org/10.1021/acscentsci.7b00303

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658761/
https://www.ncbi.nlm.nih.gov/pubmed/29104927
http://dx.doi.org/10.1021/acscentsci.7b00303

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