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, protein
- Skills
- Scientific
- 9
What it does and how to use it
A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/torchdrug && curl -fsSL https://doutorai.pt/data/lib/skills__torchdrug.md -o .claude/skills/torchdrug/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: torchdrug
description: "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."
---
# 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 pre
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