- [2024/09/17] benchmol is released on GitHub.
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Supports Property Prediction, ADMET, QSAR, Virtual Screening and More
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Supports 7 different modalities of molecules, including fingerprint, sequence, graph, geometry graph, image, geometry image, and video.
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Supports a large number of baselines for molecular data of different modalities.
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Two novel benchmarks: MBANet and StructNet.
conda create --name test_env python=3.9
pip install benchmol- If the dependencies are not automatically installed, use the following command to initialize the dependency environment:
pip install -r requirements_pip.txtBenchMol provides two new benchmarks, MBANet and StructNet.
| Name | Link | Description |
|---|---|---|
| MBANet | OneDrive | Complete MBANet data, including csv files of molecules and data of different modalities processed |
| Name | Link | Description |
|---|---|---|
| Raw Data | OneDrive | > 10 million molecules from CHEMBL 34 |
| Raw Data of StructNet | OneDrive | The original data of StructNet includes csv files of 60 datasets. |
| Processed Data of StructNet | OneDrive | Processed data, including geometry, image, video and other multi-modal data |
We provide examples of using benchmol, please see below:
The following shows a use case of extracting features from different modalities with benchmol:
| Description | Tutorial Links |
|---|---|
| Extracting Molecular Fingerprints | 1_extract_fp_features.ipynb |
| Extracting features from sequence using un-pretrained CHEM-BERT | 1_extract_sequence_features.ipynb |
| Extracting features from geometry image using IEM | 1_extract_geometry_image_features.ipynb |
| Extracting features from graph using GIN | 1_extract_graph_features.ipynb |
| Extracting features from molecular image using ImageMol | 1_extract_image_features.ipynb |
| Extracting features from video using VideoMol | 1_extract_video_features.ipynb |
Use case for linear probing is provided with benchmol: 2_linear_probing.ipynb
Use case for fine-tuning is provided with benchmol:
| Description | Tutorial Links |
|---|---|
| Fine-tuning with sequence modality | 3_fine_tuning_sequence.ipynb |
| Fine-tuning with graph modality | 3_fine_tuning_graph.ipynb |
| Fine-tuning with geometry graph modality | 3_fine_tuning_geometry.ipynb |
| Fine-tuning with image modality | 3_fine_tuning_image.ipynb |
| Fine-tuning with geometry image modality | 3_fine_tuning_geometry_image.ipynb |
| Fine-tuning with geometry video modality | 3_fine_tuning_video.ipynb |
For more information on BenchMol versions, see the Releases page.
If you find our code or anything else helpful, please do not hesitate to cite the following relevant papers: