GEN: highly efficient SMILES explorer using autodidactic generative examination networks

Recurrent neural networks have been widely used to generate millions of de novo molecules in defined chemical spaces. Reported deep generative models are exclusively based on LSTM and/or GRU units and frequently trained using canonical SMILES. In this study, we introduce Generative Examination Netwo...

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Detalles Bibliográficos
Autores principales: van Deursen, Ruud, Ertl, Peter, Tetko, Igor V., Godin, Guillaume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146994/
https://www.ncbi.nlm.nih.gov/pubmed/33430998
http://dx.doi.org/10.1186/s13321-020-00425-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146994/
https://www.ncbi.nlm.nih.gov/pubmed/33430998
http://dx.doi.org/10.1186/s13321-020-00425-8

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