geom-drugs-3dgen-evaluation
importedtherapeutics/geom-drugs-3dgen-evaluation
A refined evaluation pipeline for 3D molecular generative models trained on GEOM-Drugs.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Therapeutics
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- isayevlab
- Country
- unknown
- Homepage
- arxiv.org/abs/2505.00169
- Documentation
- unknown
- Tags
- cheminformatics · computational-chemistry · drug-discovery · generative-model · machine-learning
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- FlowMolcomputational-chemistry · drug-discovery · generative-model
Mixed continous/categorical flow-matching model for de novo molecule generation.
- Molecule-RNNcheminformatics · drug-discovery · generative-model
A recurrent neural network (RNN) that generates drug-like molecules for drug discovery.
- molgencheminformatics · drug-discovery · generative-model
Lightweight toolkit for de novo molecular generation: SMILES & SELFIES tokenizers, CharRNN / MolGPT / VAE models, training, sampling, and MOSES-style metrics.
- ALKYLcheminformatics · computational-chemistry · drug-discovery
Claude Plugin for CompChem , Drug Discovery & Organic Chemistry reasoning
- Bentocheminformatics · computational-chemistry · drug-discovery
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
- DockM8cheminformatics · computational-chemistry · drug-discovery
All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.
- api.github.com/repos/isayevlab/geom-drugs-3dgen-evaluationretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2025-09-10, 16 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/54.json→ .entries["geom-drugs-3dgen-evaluation"]
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