DI
igashov/DiffLinker
DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
372 54 +0/wk
GitHub
diffusion-models drug-design equivariance fragment-based-drug-discovery machine-learning molecular-linker
Trend
0
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
igashov/DiffLinker has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | DiffLinker | LetsFG | reward-learning-rl | brainiak |
|---|---|---|---|---|
| Stars | 372 | 372 | 373 | 370 |
| Forks | 54 | 19 | 69 | 143 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | NOASSERTION | NOASSERTION | Apache-2.0 |
Capability Radar vs LetsFG
DiffLinker
LetsFG
Maintenance Activity 0
Last code push 721 days ago.
Community Engagement 73
Fork-to-star ratio: 14.5%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.