Masked graph modeling for molecule generation
Generating new sensible molecular structures is a key problem in computer aided drug discovery. Here the authors propose a graph-based molecular generative model that outperforms previously proposed graph-based generative models of molecules and performs comparably to several SMILES-based models.
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-23415-2 |
| Summary: | Generating new sensible molecular structures is a key problem in computer aided drug discovery. Here the authors propose a graph-based molecular generative model that outperforms previously proposed graph-based generative models of molecules and performs comparably to several SMILES-based models. |
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| ISSN: | 2041-1723 |