deepchem
Builds molecular property prediction and MoleculeNet workflows with DeepChem, including SMILES featurization, scaffold or grouped holdouts, masked labels, graph models and explicit pretrained encoder transfer. Used for ADMET, toxicity, solubility and chemistry ML when DeepChem data/model contracts and scientific validation are needed.
- Version
- 2.0
- License
- MIT license
- Compatibility
- Requires Python 3.11 for the tested DeepChem 2.8.0 stack. Molecular workflows need RDKit. Torch, Transformers, torch-geometric or DGL/DGL-LifeSci depend on the chosen model. Network is needed only for package, benchmark or model downloads.
Pinned to revision 68105dd992f1, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
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Files
- skills/deepchem/SKILL.md
- skills/deepchem/SKILL_CN.md
- skills/deepchem/references/api_reference.md
- skills/deepchem/references/core_capabilities.md
- skills/deepchem/references/review.md
- skills/deepchem/references/typical_workflows.md
- skills/deepchem/references/workflows.md
- skills/deepchem/scripts/_common.py
- skills/deepchem/scripts/graph_neural_network.py
- skills/deepchem/scripts/predict_solubility.py
- skills/deepchem/scripts/transfer_learning.py
Every link opens the file at its source, pinned to the revision this page describes.