Intelligent-Drug-Discovery-Lab/MolGenBench
Codebase for Paper: Benchmarking Real-World Applicability of Molecular Generative Models from De novo Design to Lead Optimization with MolGenBench
32
Stars
1
Forks
22.9
Radar Score
Stable
Momentum
Scoring Breakdown
Impact9.3
Velocity22.1
Health45.9
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Jupyter Notebook
Why it ranks
Modest but positive momentum.
Top 94% globally
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
B
Based on maintenance, issue response, and release cadence.
Radar Score
22.9
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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