在模拟中量化跨膜应力和力矩的不确定性。

4区 生物学 Q3 Biochemistry, Genetics and Molecular Biology
Methods in enzymology Pub Date : 2024-01-01 Epub Date: 2024-05-17 DOI:10.1016/bs.mie.2024.04.008
Samuel L Foley, Markus Deserno
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引用次数: 0

摘要

脂质双分子层的横向应力曲线是分子模拟与介观弹性理论之间的重要纽带。尽管它经常在模拟中被计算出来,但其统计精度(或由其推导出的观测值的统计精度)往往没有明确说明。这种疏忽可能会造成问题,因为不确定性是评估统计意义的先决条件。在本章中,我们将对横向应力剖面的统计误差分析进行全面而简明的概述。我们详细介绍了两种相对简单但功能强大的误差条生成技术:块平均法和引导法。结合这些方法,我们可以可靠地估计不确定性,即使在模拟数据中普遍存在的时间和空间相关性的情况下也是如此。我们用简单的例子(如应力矩),以及更复杂的观测指标(如应力曲线极值的位置和单层中性面)来说明这些技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying uncertainty in trans-membrane stresses and moments in simulation.

The lateral stress profile of a lipid bilayer constitutes a valuable link between molecular simulation and mesoscopic elastic theory. Even though it is frequently calculated in simulations, its statistical precision (or that of observables derived from it) is often left unspecified. This omission can be problematic, as uncertainties are prerequisite to assessing statistical significance. In this chapter, we provide a comprehensive yet accessible overview of the statistical error analysis for the lateral stress profile. We detail two relatively simple but powerful techniques for generating error bars: block-averaging and bootstrapping. Combining these methods allows us to reliably estimate uncertainties, even in the presence of both temporal and spatial correlations, which are ubiquitous in simulation data. We illustrate these techniques with simple examples like stress moments, but also more complex observables such as the location of stress profile extrema and the monolayer neutral surface.

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来源期刊
Methods in enzymology
Methods in enzymology 生物-生化研究方法
CiteScore
2.90
自引率
0.00%
发文量
308
审稿时长
3-6 weeks
期刊介绍: The critically acclaimed laboratory standard for almost 50 years, Methods in Enzymology is one of the most highly respected publications in the field of biochemistry. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 500 volumes the series contains much material still relevant today and is truly an essential publication for researchers in all fields of life sciences, including microbiology, biochemistry, cancer research and genetics-just to name a few. Five of the 2013 Nobel Laureates have edited or contributed to volumes of MIE.
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