DLS5-Omics/GEMGen
A generative model for phenotypic-based drug discovery
This tool helps drug discovery scientists generate novel small molecule candidates based on desired cellular effects. You input information about a cell type and a list of genes you want to see either increase or decrease in expression. The tool then outputs potential small molecule structures (SMILES strings) that could induce those changes, and scores how well they match your desired phenotype. This is for researchers in pharmaceutical or academic settings focused on early-stage drug discovery and lead generation.
Use this if you need to rapidly explore and generate new small molecule drug candidates that target specific cellular pathways or phenotypes without extensive wet-lab experimentation.
Not ideal if you are looking for a tool to synthesize or experimentally validate molecules, or if you need to predict pharmacokinetic properties or toxicity.
Stars
9
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
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