Torchdrug
원문: torchdrug
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.
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TorchDrug Overview TorchDrug is a comprehensive PyTorch based machine learning toolbox for drug discovery and molecular science. Apply graph neural networks, pre trained models, and task definitions to molecules, proteins, and biological knowledge graphs, including molecular property prediction, protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis planning, with 40+ curated datasets and 20+ model architectures. When to Use This Skill This skill should be used when working with: Data Types: SMILES strings or molecular structures Protein sequences or 3D structures (PDB files) Chemical reactions and retrosynthesis Biomedical knowledge graphs Drug discovery datasets …
실행 시 본인 API 키(BYOK)로 동작하며, 모델 비용은 사용자 계정에서 직접 결제됩니다.