Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center

Effective synthesis planning powered by deep learning (DL) can significantly accelerate the discovery of new drugs and materials. However, most DL-assisted synthesis planning methods offer either none or very limited capability to recommend suitable reaction conditions (RCs) for their reaction predi...

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Detalles Bibliográficos
Autores principales: Wang, Xiaorui, Hsieh, Chang-Yu, Yin, Xiaodan, Wang, Jike, Li, Yuquan, Deng, Yafeng, Jiang, Dejun, Wu, Zhenxing, Du, Hongyan, Chen, Hongming, Li, Yun, Liu, Huanxiang, Wang, Yuwei, Luo, Pei, Hou, Tingjun, Yao, Xiaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578430/
https://www.ncbi.nlm.nih.gov/pubmed/37849643
http://dx.doi.org/10.34133/research.0231

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578430/
https://www.ncbi.nlm.nih.gov/pubmed/37849643
http://dx.doi.org/10.34133/research.0231

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