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HypoGeniC

Maintainer K-Dense Inc. · Last updated April 1, 2026

Hypogenic provides automated hypothesis generation and testing using large language models to accelerate scientific discovery. The framework supports three approaches: HypoGeniC (data-driven hypothesis generation), HypoRefine (synergistic literature and data integration), and Union methods (mechanistic combination of literature and data-driven hypotheses).

Claude CodeOpenClawNanoClawAnalysisReproductionhypogenicmulti-omicspackagemulti-omics & ai agent frameworks

Original source

K-Dense-AI/claude-scientific-skills

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypogenic

Maintainer: K-Dense Inc.
License: MIT license
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

Hypogenic provides automated hypothesis generation and testing using large language models to accelerate scientific discovery. The framework supports three approaches: HypoGeniC (data-driven hypothesis generation), HypoRefine (synergistic literature and data integration), and Union methods (mechanistic combination of literature and data-driven hypotheses).
uv pip install hypogenic.

Source Doc

Excerpt From SKILL.md

Quick Start

Get started with Hypogenic in minutes:


## Clone example datasets

git clone https://github.com/ChicagoHAI/HypoGeniC-datasets.git ./data

## Run basic hypothesis generation

hypogenic_generation --config ./data/your_task/config.yaml --method hypogenic --num_hypotheses 20

Use cases

Generating scientific hypotheses from observational datasets.
Testing multiple competing hypotheses systematically.
Combining literature insights with empirical patterns.
Accelerating research discovery through automated hypothesis ideation.

Not for

Do not rely on this catalog entry alone for installation or maintenance details.

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