Predict molecular properties with graph neural networks using PyTorch.
npx skills add https://github.com/sanand0/scientific-research --skill torchdrug-sanand0
Please help me install this Agent Skill. Skill: torchdrug Source: https://github.com/sanand0/scientific-research/tree/main/.claude/skills/torchdrug Command: npx skills add https://github.com/sanand0/scientific-research --skill torchdrug-sanand0
This Skill provides a comprehensive toolkit for applying machine learning, particularly graph neural networks, to complex problems in drug discovery and molecular science, streamlining research and development.
Use the torchdrug skill to predict molecular properties using the BBBP dataset and a GIN model.
High-intent search queries and answers about installing and using this skill.
To predict molecular properties like ADMET using graph neural networks, you can use this Skill to load molecular structures and apply PyTorch-based GIN models to datasets like BBBP for accurate predictions.
Yes, you can use PyTorch to plan retrosynthesis and generate novel molecules by leveraging this Skill's graph-based modeling capabilities to design structures and map out their synthesis pathways.
Yes, you need RDKit integration to perform molecular modeling and protein analysis, as this Skill requires cheminformatics libraries alongside deep learning frameworks to process molecular structures.
The best way to discover drug repurposing opportunities using knowledge graphs is by applying this Skill's reasoning capabilities to analyze disease mechanisms and identify novel drug-target interactions.
biomaps-infraDevelop drug discovery AI models with PyTorch-native graph neural networks.
liongkjApply computational chemistry methods to predict molecular properties and reaction pathways.
Yezez9Develop custom GNN architectures for molecular and protein data analysis with PyTorch.
biomaps-infraTrains and applies DeepChem machine learning models for molecular property prediction.
