用于系统生物学中预测不确定性定量化的光谱扩展方法
Anna Deneer1, Jaap Molenaar1, Christian Fleck2
1Mathematical and Statistical Methods Group, Wageningen University and Research, Wageningen, Netherlands.
Frontiers in systems biology
|August 14, 2025
概括
本研究引入了一种新的光谱扩展 (SE) 方法,以有效量化复杂生物模型中的预测不确定性. 新方案通过最大限度地减少模型评估来显著降低计算成本,这对于随机系统至关重要.
科学领域:
- 系统生物学 系统生物学
- 计算数学 计算数学 计算数学
- 随机系统 随机系统 随机系统
背景情况:
- 由于基因表达噪声等因素,生物系统表现出固有的不确定性.
- 随机系统的预测模型必须考虑到参数的变化.
- 量化参数不确定性如何影响模型预测对于实验设计等应用至关重要.
研究的目的:
- 开发一种有效的方法来计算光谱扩张 (SE) 系数.
- 在复杂模型中减少与量化预测不确定性相关的计算成本.
- 为了实现准确的不确定性量化,即使在具有挑战性的场景,如高计算成本,分叉和不连续性.
主要方法:
- 开发了一种用于计算光谱膨胀系数的创新方案.
- 确保所需的模型评估数量有限.
- 将该方案应用于各种例子,包括缓慢收的复杂模型.
主要成果:
- 拟议的SE方案大大减少了需要的模型评估的数量.
- 这带来了实质性的计算优势,特别是在高度复杂的模型中.
- 该方法有效地处理具有挑战性的情况,证明了它的力量和效率.
结论:
- 新的SE方案为系统生物学中的不确定性量化提供了一种高效和强大的方法.
- 它克服了传统方法的局限性,例如蒙特卡洛对于计算上昂贵的模型.
- 这一进步促进了生物研究中更可靠的基于模型的决策.
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