skills/claude-scientific-skills
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Timothy Kassis
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scientific-packages/deepchem/SKILL.md
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name: deepchem
description: Comprehensive toolkit for molecular machine learning, drug discovery, and materials science using DeepChem. Use this skill when working with molecular data (SMILES, SDF files), predicting molecular properties (solubility, toxicity, binding affinity), training graph neural networks on molecules, using MoleculeNet benchmarks, performing molecular featurization, or applying transfer learning with pretrained chemical models (ChemBERTa, GROVER). Also applicable for materials science (crystal structures, bandgap prediction) and protein/DNA sequence analysis.
description: DeepChem toolkit for molecular machine learning, drug discovery, and materials science. Use for: molecular property prediction (solubility, toxicity, ADMET, binding affinity, drug-likeness), molecular featurization (fingerprints, descriptors, graph representations), graph neural networks (GCN, GAT, MPNN, AttentiveFP, DMPNN), MoleculeNet benchmark datasets (Tox21, BBBP, Delaney, HIV, ClinTox, FreeSolv, Lipophilicity), transfer learning with pretrained models (ChemBERTa, GROVER, MolFormer), materials property prediction (crystal structures, bandgap, formation energy), protein/DNA sequence analysis, molecular data loading (SMILES, SDF, FASTA), scaffold-based data splitting, molecular generation, hyperparameter optimization, model evaluation and comparison, custom model integration, and end-to-end drug discovery workflows.
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# DeepChem