GROVER is a self-supervised Graph Neural Network for molecular representation pretrained with 10 million unlabelled molecules from ChEMBL and ZINC15. The model provided has been pre-trained on 10 million molecules (GROVERlarge). GROVER has then been fine-tuned to predict several activities from the MoleculeNet benchmark, consistently outperforming other state-of-the-art methods for serveral benchmark datasets.
- EOS model ID:
eos7w6n - Slug:
grover-embedding
- Input:
Compound - Input Shape:
Single - Task:
Representation - Output:
Descriptor - Output Type:
Float - Output Shape:
List - Interpretation: Embedding representation of a molecule
- Publication
- Source Code
- Ersilia contributor: miquelduranfrigola
If you use this model, please cite the original authors of the model and the Ersilia Model Hub.
This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a MIT license.
Notice: Ersilia grants access to these models 'as is' provided by the original authors, please refer to the original code repository and/or publication if you use the model in your research.
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