Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For ready-made ADMET numbers without training a model use admet-prediction; for benchmark datasets and task-aware splits use pytdc.
At a glance
This skill is for Presentations and helps you predict molecular properties with machine learning, featurize molecular structures, and benchmark drug discovery models.
git clone --depth 1 https://github.com/K-Dense-AI/drug-discovery-agent-skills
cp -r drug-discovery-agent-skills/skills/deepchem ~/.claude/skills/deepchem
Molecular MlcheminformaticsGraph Neural Networksdrug-discoveryFeaturizationadmet
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