repoGitHubTrust 82 · PrimaryPublished 9d agoLive · 9d ago
mqcomplab/MDANCE
MDANCE: Hyper-efficient tools to process molecular dynamics simulations.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 55%Bridging the NISQ and Fault-Tolerant Regimes: Generative-ML-Assisted Quantum Selected CI for Molecular Simulations →
- PossiblePossibly related (embedding) · 54%Bridging three-dimensional molecular structures and artificial intelligence with a conformation description language →
- PossiblePossibly related (embedding) · 53%SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles →
- PossiblePossibly related (embedding) · 51%Reshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1 →
- PossiblePossibly related (embedding) · 49%Efficient and valid large molecule generation via self-supervised generative models - Nature →
Implements
Covers
newsBridging three-dimensional molecular structures and artificial intelligence with a conformation description languagenewsReshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1newsEfficient and valid large molecule generation via self-supervised generative models - Nature
Related across the graph
paperSynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore ProfilespaperBridging the NISQ and Fault-Tolerant Regimes: Generative-ML-Assisted Quantum Selected CI for Molecular SimulationsnewsEfficient and valid large molecule generation via self-supervised generative models - NaturenewsReshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1newsBridging three-dimensional molecular structures and artificial intelligence with a conformation description language