Jupyter_Dock
importedprotocols/jupyter-dock
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Protocols & Guidelines
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/AngelRuizMoreno/Jupyter_Dock
- Documentation
- unknown
- Tags
- autodock · autodock-vina · cheminformatics · computational-biology · drug-design · drug-discovery · drug-repurposing · jupyter-notebook
- 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.
- bitbirchcheminformatics · drug-design · drug-discovery · drug-repurposing
BitBIRCH clustering algorithm
- labodockautodock-vina · cheminformatics · drug-design
LABODOCK: A Colab-Based Molecular Docking Tools
- CANDOdrug-design · drug-discovery · drug-repurposing
Computational Analysis of Novel Drug Opportunities
- DrugClawdrug-design · drug-discovery · drug-repurposing
💊 AI Research Assistant for Accelerated Drug Discovery. 🦞
- LaBOXautodock-vina · drug-design
LaBOX: A Grid Box Calculation Tool for Molecular Docking
- molecular-vaecheminformatics · drug-discovery · jupyter-notebook
Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"
- api.github.com/repos/AngelRuizMoreno/Jupyter_Dockretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-10-30, 285 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/38.json→ .entries["jupyter-dock"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.