ml-drug-discovery
importedtherapeutics/ml-drug-discovery
The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Therapeutics
- Subcategory
- unknown
- License
- Apache-2.0(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Repository
- github.com/nrflynn2/ml-drug-discovery
- Documentation
- unknown
- Tags
- ai · cheminformatics · deep-learning · drug-discovery · machine-learning · medicinal-chemistry · medicine-applications · notebooks
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- datamolcheminformatics · drug-discovery · medicinal-chemistry
Molecular Processing Made Easy.
- radiology-swarmmedicine-applications
A powerful, enterprise-grade multi-agent system for advanced radiological analysis, diagnosis, and treatment planning. This system leverages specialized AI agents working in concert to provide…
- Bentocheminformatics · drug-discovery
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
- bitbirchcheminformatics · drug-discovery
BitBIRCH clustering algorithm
- dgl-lifescicheminformatics · drug-discovery
Python package for graph neural networks in chemistry and biology
- DockM8cheminformatics · drug-discovery
All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.
- api.github.com/repos/nrflynn2/ml-drug-discoveryretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-07-29, 94 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/58.json→ .entries["ml-drug-discovery"]
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