DSPsleeporg/smiles-transformer
Original implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.
This project helps chemists and drug discovery researchers translate chemical molecule structures (represented as SMILES strings) into numerical 'fingerprints' that capture their key properties. It takes SMILES strings as input and outputs these molecular fingerprints, which are useful for various computational chemistry tasks. This is ideal for scientists working on early-stage drug discovery or materials science who need to analyze and compare molecular properties efficiently.
354 stars. No commits in the last 6 months.
Use this if you need to generate numerical representations of chemical molecules from their SMILES strings to accelerate tasks like drug screening or property prediction.
Not ideal if you are looking for a tool to synthesize molecules or perform quantum chemistry simulations, as this focuses solely on generating molecular fingerprints.
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354
Forks
63
Language
Jupyter Notebook
License
MIT
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Last pushed
Dec 22, 2022
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