nrflynn2/ml-drug-discovery
The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)
This project provides practical code examples and datasets to help chemists and pharmaceutical researchers apply machine learning to accelerate drug discovery. It takes raw chemical data and biological assay results, applying various machine learning techniques to predict properties, identify promising compounds, and design new molecules. Medicinal chemists, computational chemists, and researchers in pharmaceutical R&D would find this valuable.
Use this if you are a drug discovery scientist looking to understand and implement machine learning and deep learning techniques for tasks like ligand-based screening, predicting molecular properties, or generating new molecular structures.
Not ideal if you are looking for a standalone software tool or a black-box solution, as this repository is designed as a companion to a textbook and requires understanding the underlying concepts.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Jan 09, 2026
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