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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...
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical Society
2017
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| 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 |