Soft Modes as a Predictive Framework for Low-Dimensional Biological Systems Across Scales.

IF 10.4 1区 生物学 Q1 BIOPHYSICS
Christopher Joel Russo, Kabir Husain, Arvind Murugan
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引用次数: 0

Abstract

All biological systems are subject to perturbations arising from thermal fluctuations, external environments, or mutations. Yet, while biological systems consist of thousands of interacting components, recent high-throughput experiments have shown that their response to perturbations is surprisingly low dimensional: confined to only a few stereotyped changes out of the many possible. In this review, we explore a unifying dynamical systems framework-soft modes-to explain and analyze low dimensionality in biology, from molecules to ecosystems. We argue that this soft mode framework makes nontrivial predictions that generalize classic ideas from developmental biology to disparate systems, namely phenocopying, dual buffering, and global epistasis. While some of these predictions have been borne out in experiments, we discuss how soft modes allow for a surprisingly far-reaching and unifying framework in which to analyze data from protein biophysics to microbial ecology.

软模式作为跨尺度低维生物系统的预测框架
所有的生物系统都会受到由热波动、外部环境或突变引起的扰动。然而,尽管生物系统由数千个相互作用的组件组成,但最近的高通量实验表明,它们对扰动的反应是惊人的低维:局限于许多可能的变化中的少数几种定型变化。在这篇综述中,我们探索了一个统一的动力系统框架-软模式-来解释和分析生物学中的低维,从分子到生态系统。我们认为,这种软模式框架做出了重要的预测,将经典的思想从发育生物学推广到不同的系统,即表型复制、双重缓冲和全局上位。虽然这些预测中的一些已经在实验中得到证实,但我们讨论了软模式如何允许一个令人惊讶的深远和统一的框架,在这个框架中分析从蛋白质生物物理学到微生物生态学的数据。
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来源期刊
Annual Review of Biophysics
Annual Review of Biophysics 生物-生物物理
CiteScore
21.00
自引率
0.00%
发文量
25
期刊介绍: The Annual Review of Biophysics, in publication since 1972, covers significant developments in the field of biophysics, including macromolecular structure, function and dynamics, theoretical and computational biophysics, molecular biophysics of the cell, physical systems biology, membrane biophysics, biotechnology, nanotechnology, and emerging techniques.
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