GRAPH-0/CDGS
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
This project helps chemists and drug discovery scientists by generating novel molecular structures. You input chemical properties or desired characteristics, and it outputs a diverse set of new molecular graphs that fit those conditions. It is ideal for researchers in fields like medicinal chemistry or materials science who need to explore potential compounds.
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Use this if you need to computationally design new molecules with specific properties for drug discovery, material science, or chemical research.
Not ideal if you are looking to analyze existing molecular data or predict properties of known compounds rather than generate new ones.
Stars
36
Forks
3
Language
Python
License
—
Category
Last pushed
Jun 11, 2023
Commits (30d)
0
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