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blatant-why

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therapeutics/blatant-why

AI-powered biologics design campaign agent — multi-agent orchestration with BoltzGen, PXDesign, Protenix, and 200+ cloud tools. Antibodies, nanobodies, de novo binders, and beyond.

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Therapeutics
Subcategory
unknown
License
MIT(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
ai-agent · antibody-design · boltzgen · claude-code · computational-biology · drug-discovery · mcp-server · protein-engineering
Regulatory
unknown
built by · 1

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.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • boltzgenantibody-design · drug-discovery

    BoltzGen: Toward Universal Binder Design

  • dyMEANantibody-design · drug-discovery

    This repo contains the codes for our paper "End-to-End Full-Atom Antibody Design"

  • MEANantibody-design · drug-discovery

    This repo contains the codes for our paper Conditional Antibody Design as 3D Equivariant Graph Translation.

  • lifesciences-researchclaude-code · computational-biology · drug-discovery

    AI Agent wrappers for Life Sciences APIs (Open Targets, ChEMBL, UniProt). Accelerating drug discovery with Model Context Protocol (MCP) and FastMCP.

  • lrDMS-IREDprotein-engineering

    Code, data and notebooks for engineering enzymes with ultra-high throughput microfluidics. Please read our accompanying paper for details.

  • k-dense-byokai-agent · drug-discovery

    An AI co-scientist powered by Scientific Agent Skills running on your desktop.

sources
  1. api.github.com/repos/001TMF/blatant-why
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-05-21, 104 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

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machine-readable

/v1/entries/48.json→ .entries["blatant-why"]

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