通过人工智能实现自然语言处理和合成遗传电路设计
Lucas Abello Castillo1, Martín Gutiérrez Pescarmona1
1Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército Libertador 441, 8370191 Santiago, RM, Chile.
ACS synthetic biology
|September 4, 2025
概括
这项研究介绍了CELLM,一个将大型语言模型与Cello等合成生物学工具集成的新系统. 它通过自然语言实现了基因电路设计,使合成生物学更容易获得.
科学领域:
- 合成生物学
- 计算生物学
- 生物信息学
背景情况:
- 遗传电路设计复杂, 阻碍合成生物学的可访问性和效率.
- 目前的设计工具需要专门的生物工程专业知识.
研究的目的:
- 使用自然语言指令创建,分析和优化遗传电路的综合系统 (CELLM).
- 弥合自然语言处理与功能生物设计之间的差距.
主要方法:
- 通过Python中的LangChain框架将Cello软件 (v2.1) 与大型语言模型 (DeepSeek-R1, Phi-4) 集成.
- 将文本描述自动翻译成遗传电路设计.
- 使用LLM来解释生物要求并进行逻辑优化.
主要成果:
- 展示了第一个将LLM与Cello等合成生物学设计工具集成的系统.
- 自然语言的成功翻译促使我们设计出功能性的遗传电路.
- CELLM自动化了电路合成和优化过程.
结论:
- CELLM为在合成生物学设计中使用LLM创造了先例.
- 该系统显著降低了基因电路原型的进入障碍.
- 这种方法提高了合成生物学研究的效率和可访问性.
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