ersilia-os/chempfn

Ensemble-based, size-agnostic wrapper for the TabPFN classifier

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Experimental

This project helps medicinal chemists and cheminformaticians classify chemical compounds based on their molecular structure. You provide a list of chemical structures (SMILES data), and it predicts a category or property for each, such as whether a compound is antimicrobial. It's designed for researchers working with chemical datasets who need fast, accurate classification without extensive model tuning.

No commits in the last 6 months.

Use this if you need to quickly classify chemical compounds from SMILES data into distinct categories, especially for small-to-medium datasets, without manually featurizing your molecules.

Not ideal if you require extremely fast prediction times for very large datasets, as prediction speed can vary depending on configuration and hardware.

medicinal-chemistry cheminformatics drug-discovery compound-classification antimicrobial-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 3 / 25

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Language

Jupyter Notebook

License

GPL-3.0

Last pushed

May 18, 2024

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