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生物模型存储库的验证和可重复的策划
Lucian P Smith1, Rahuman S Malik-Sheriff2, Tung V N Nguyen2
1Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.
PLoS computational biology
|December 4, 2025
概括
我们通过纠正和生成模拟实验描述标记语言 (SED-ML) 文件,提高了BioModels数据库中的1000多个机械模型的可重复性,从而提高了模型的可重复使用性.
科学领域:
- 计算生物学 计算生物学
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
背景情况:
- 生物模型存储库拥有超过1000个精心策划的机械模型,主要是系统生物学标记语言 (SBML).
- SBML正式指定模型,但缺乏计算实验条件,阻碍了结果的可复制性.
- 模拟实验描述标记语言 (SED-ML) 标准化了模型模拟的实验规格.
研究的目的:
- 提高生物模型数据库中策划的机械模型的可复制性和可重复使用性.
- 更新,纠正和生成模拟实验描述标记语言 (SED-ML) 文件,用于1055个模型.
- 使用SED-ML验证多个生物模拟引擎的模拟结果.
主要方法:
- 更新和纠正超过450个生物模型条目的现有SED-ML文件.
- 为剩余的生物模型条目生成了新的SED-ML文件.
- 使用包装架构用于SED-ML解释和交叉引擎验证,使用五个基于ODE的生物仿真引擎.
主要成果:
- 成功更新/纠正/生成了1055个策划的机械模型的SED-ML文件.
- 在多个基于ODE的生物模拟引擎中验证了模拟一致性.
- 在现有的SED-ML文件和模拟引擎中识别并解决了问题.
结论:
- 改进的SED-ML文件显著提高了生物模型的可复制性和可信性.
- 增强的模型可复制性增加了它们对新研究和多尺度建模的实用性.
- 标准化的模拟实验有助于跨平台验证和模型重复使用.
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