benstaf/ChemGAN-challenge
Code for the paper: ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.
This project helps drug discovery researchers generate new chemical structures with desired properties, potentially leading to novel drug candidates. By inputting a set of known chemical compounds, it outputs a diverse collection of entirely new molecular structures. Medicinal chemists and computational chemists can use this to explore a broader chemical space.
115 stars. No commits in the last 6 months.
Use this if you are a drug discovery researcher looking to generate novel chemical compound designs for therapeutic development.
Not ideal if you need to synthesize or test existing compounds, as this tool focuses purely on generating new molecular structures.
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Python
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Last pushed
Mar 24, 2023
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