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A self-attention based message passing neural network for predicting molecular lipophilicity and aqueous solubility
Efficient and accurate prediction of molecular properties, such as lipophilicity and solubility, is highly desirable for rational compound design in chemical and pharmaceutical industries. To this end, we build and apply a graph-neural-network framework called self-attention-based message-passing ne...
Autores principales: | Tang, Bowen, Kramer, Skyler T., Fang, Meijuan, Qiu, Yingkun, Wu, Zhen, Xu, Dong |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035778/ https://www.ncbi.nlm.nih.gov/pubmed/33431047 http://dx.doi.org/10.1186/s13321-020-0414-z |
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