Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation

Today more and more data are freely available. Based on these big datasets deep neural networks (DNNs) rapidly gain relevance in computational chemistry. Here, we explore the potential of DNNs to predict chemical properties from chemical structures. We have selected the octanol-water partition coeff...

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Detalles Bibliográficos
Autores principales: Ulrich, Nadin, Goss, Kai-Uwe, Ebert, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814212/
https://www.ncbi.nlm.nih.gov/pubmed/36697535
http://dx.doi.org/10.1038/s42004-021-00528-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814212/
https://www.ncbi.nlm.nih.gov/pubmed/36697535
http://dx.doi.org/10.1038/s42004-021-00528-9

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