TorchDrug
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About
TorchDrug is a comprehensive machine learning platform specifically developed for drug discovery. It integrates advanced techniques such as graph machine learning (including graph neural networks, geometric deep learning, and knowledge graphs), deep generative models, and reinforcement learning. The platform offers a flexible interface for rapid prototyping of drug discovery models within PyTorch. It aims to make drug discovery techniques accessible, allowing machine learning practitioners to apply fundamental algorithms with minimal effort on domain-specific knowledge. Key features include minimal domain knowledge requirements, a large collection of datasets and building blocks for fast iteration, comprehensive benchmarks for model comparison, and scalable training and inference across various hardware configurations. TorchDrug was initiated by MilaGraph to accelerate development and integrate recent advances in the field.
Platform
Task
Features
• scalable training and inference
• comprehensive benchmarks
• datasets and building blocks
• minimal domain knowledge
• biomedical knowledge graph reasoning
• reaction prediction & retrosynthesis
• de novo molecule design & optimization
• property prediction
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