akensert/molgraph
Graph neural networks for molecular machine learning: Implemented and compatible with TensorFlow and Keras.
This project helps computational chemists and cheminformaticians build predictive models for molecular properties. It takes molecular structures as input and outputs predictions, such as a molecule's binding affinity or toxicity. Researchers can use this to explore new drug candidates or understand chemical reactions.
Available on PyPI.
Use this if you need to build or benchmark graph neural networks for molecular machine learning applications, especially within the TensorFlow/Keras ecosystem.
Not ideal if you are looking for a pre-built, ready-to-use tool for general molecule prediction without needing to configure or train a machine learning model.
Stars
62
Forks
5
Language
Python
License
MIT
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
5
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