SGGRL: Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry
Dear Colleagues,
I apologize for the delay in responding to your queries. I've been preoccupied with my regular workload. I'll address these issues as soon as possible. Sorry for any inconvenience this may have caused.
Best regards,
Zeyu Wang
- paddle-bfloat==0.1.7
- paddlepaddle==2.5.1
- torch==1.13.0
- torch-cluster==1.6.0+pt113cu117
- torch-geometric==2.2.0
- torch-scatter==2.1.0+pt113cu117
- torch-sparse==0.6.15+pt113cu117
- torch-spline-conv==1.2.1+pt113cu117
- rdkit==2023.3.1
- Process Data
python build_corpus.py --in_path {data_path} --out_path {save_path}
python build_vocab.py --corpus_path {corpus_path} --out_path {save_path}
python data_3d.py --dataset {dataset name}
- Molecular Property Prediction
python main.py --dataset {dataset name} --task_type {reg/class}
Wang Z, Jiang T, Wang J, et al. Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry[J]. arXiv preprint arXiv:2401.03369, 2024.