ML+AI frameworks for chemistry

• AIRS: AIRS is a collection of open-source software tools, datasets, and benchmarks associated with our paper entitled “Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems”
  
  
  
• AMPL: A Data-Driven Modeling Pipeline for Drug Discovery (ATOM Modeling PipeLine) (standalone)
  
  
  
• cgcnn:
  
  
  
• chainer-chemistry:
  
  
  
• ChemML:
  
  
  
• chemml:
  
  
  
• chemprop:
  
  
  
• DeepChem:
  
  
  
• DeepMol: a python-based machine and deep learning framework for drug discovery (standalone)
  
  
  
• DGL-LifeSci:
  
  
  
• Minervachem:
  
  
  
• Minerva-Chem:
  
  
  
• MolFlux:
  
  
  
• MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery (needs registration) (online, 2024).
  
• olorenchemengine:
  
  
• OpenChem:
  
  
  
• pytorch-geometric:
  
• Scikit-mol: Scikit-Learn classes for molecular vectorization using RDKit (standalone)
  
  
  
• Summit:
  
  
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• TorchDrug: A powerful and flexible machine learning platform for drug discovery
  
  
  
  
• DeepMol:
  
  
  
• MolPipeline: