Cargando…
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...
| Autores principales: | , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2020
|
| Materias: | |
| 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 |