Cargando…
Exploring the GDB-13 chemical space using deep generative models
Recent applications of recurrent neural networks (RNN) enable training models that sample the chemical space. In this study we train RNN with molecular string representations (SMILES) with a subset of the enumerated database GDB-13 (975 million molecules). We show that a model trained with 1 million...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2019
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419837/ https://www.ncbi.nlm.nih.gov/pubmed/30868314 http://dx.doi.org/10.1186/s13321-019-0341-z |