AA
AAV vector design: capsid selection, promoter optimization, payload capacity.
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数据与复现
ME
medea-therapeutic-discovery
维护者 FreedomIntelligence · 最近更新 2026年4月1日
An AI agent for therapeutic discovery that executes transparent, multi-step omics analyses including research planning, code execution, and literature reasoning.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/medea-therapeutic-discovery
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Medea是一个multi-stage AI agent designed ，用于 therapeutic discovery，modeled after 2026 state-of- -art open source architectures. It executes transparent，multi-step omics analyses。
- 运行 multi-omics therapeutic discovery pipeline。
- 分析 omics data ，用于 novel drug targets ，使用 Medea。
- 执行 literature reasoning 、 consensus reconciliation ，用于 target X。
- 运行 multi-omics therapeutic discovery pipeline" "Analyze omics data ，用于 novel drug targets ，使用 Medea" * "Perform literature reasoning 、 consensus reconciliation ，用于 target X。
原始文档
SKILL.md 摘录
Core Capabilities
- Research Planning: Formulates step-by-step omics analysis plans.
- Code Execution: Generates and executes Python/R scripts for data processing.
- Literature Reasoning: Retrieves and synthesizes current literature.
- Consensus Stage: Reconciles experimental evidence with literature to propose high-confidence targets.
Workflow
- Step 1: Initialize Medea agent with target disease or omics dataset.
- Step 2: Execute the multi-stage pipeline across planning, coding, literature review, and consensus validation.
Example Usage
User: "Run Medea analysis on the provided breast cancer multi-omics dataset."
Agent Action:
适用场景
- 运行 multi-omics therapeutic discovery pipeline。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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