Talk2Biomodels:基于人工智能代理的开源LLM倡议,用于动态生物模型
Lilija Wehling1, Gurdeep Singh2, Ahmad Wisnu Mulyadi2
1BioMed X Institute, Heidelberg, Germany. wehling@bmedx.com.
BMC bioinformatics
|November 19, 2025
概括
Talk2Biomodels (T2B) 是一个新的AI平台,它简化了使用自然语言对话访问和分析生物模型. 该工具使复杂系统生物学模型更容易获得专家和非专家,促进公平的数据原则.
科学领域:
- 系统生物学 系统生物学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 定量运动模型对于了解疾病机制至关重要,但需要专门的专业知识来进行模拟和分析.
- 访问和解释复杂的生物模型对没有广泛的计算培训的研究人员来说是一个重大障碍.
研究的目的:
- 介绍Talk2Biomodels (T2B),一个旨在民主化对生物系统计算模型的访问的AI平台.
- 在系统生物学研究中促进FAIRification (可查找性,可访问性,互操作性,可重复使用性) 原则.
- 使用户能够通过自然语言对话与生物模型进行交互和分析.
主要方法:
- 开发一个开源,用户友好的,基于大型语言模型的代理人工智能平台 (Talk2Biomodels).
- 与生物模型数据库集成,用于检索,模拟和分析策划的系统生物学模型.
- 支持用系统生物学标记语言 (SBML) 编码的模型.
主要成果:
- Talk2Biomodels允许自然语言交互,降低模型解释和假设驱动探索的进入障碍.
- 该平台在与精准医学,传染病流行病学和蜂系统相关的用例中成功展示了其能力.
- 无论是计算专家还是没有先前建模培训的领域科学家,都可以从使用T2B的复杂生物模型中获得可操作的见解.
结论:
- Talk2Biomodels显著降低了非专家参与计算生物模型的障碍.
- 该平台为专家提供了一个精简的界面来分析模型,提高效率.
- T2B有助于生物模型的整体 FAIRification,提高其可访问性和可重复使用性.
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