Build and train graph neural network models on molecular and protein data.
npx skills add https://github.com/swaruplab/operon --skill torchdrug-swaruplab
Please help me install this Agent Skill. Skill: torchdrug Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/torchdrug Command: npx skills add https://github.com/swaruplab/operon --skill torchdrug-swaruplab
TorchDrug enables researchers to rapidly build, train, and deploy graph neural network models for molecular and protein data, supporting property prediction, molecule generation, and knowledge-graph reasoning in a single framework.
Load a molecular dataset and train a graph-based property prediction task using a GIN backbone.
High-intent search queries and answers about installing and using this skill.
Train graph neural networks for molecular property prediction by loading a molecular dataset and using a modular GIN or GCN backbone within an end-to-end pipeline that includes training loops and evaluation metrics.
Graph neural networks support protein modeling and knowledge-graph reasoning by providing architectures like GearNet to reason over biomedical knowledge graphs and predict protein properties.
Build a drug discovery pipeline for retrosynthesis and molecule generation using a modular API with pre-built architectures, dataset access, task wrappers, and reproducibility tools to enable reproducible research.
The framework enables seamless data interoperability with RDKit for molecular structures and integrates with structure predictors like AlphaFold and ESM for protein data processing.
Available graph neural network architectures include GIN, GCN, GAT, SchNet, and GearNet, specifically designed for processing molecular and protein graph structures.
Using a single framework for molecule generation and knowledge-graph reasoning allows researchers to rapidly build, train, and deploy models using a modular API with shared datasets, tasks, and evaluation metrics.
jackspaceApply graph neural networks to drug discovery tasks with PyTorch.
jimmc414Predict molecular properties from SMILES strings using a PyTorch-based toolkit.
LeonChaoXTrain PyTorch-native graph neural networks on TorchDrug datasets for molecular and protein tasks.
LogauaEngstromBuild graph-based drug discovery models for molecular property prediction and retrosynthesis planning.
