DeepChem

Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks. Use when running end-to-end molecular ML experiments that need MoleculeNet benchmarks, scaffold splitting, or ready-made models with minimal setup; for building custom PyTorch graph architectures prefer alterlab-torch-geometric, and for standalone molecule-to-feature-vector generation prefer alterlab-molfeat. Part of the AlterLab Academic Skills suite.