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arXiv · 2412.13637

Soft Modes as a Predictive Framework for Low Dimensional Biological Systems across Scales

Christopher Joel Russo·Kabir Husain·Arvind Murugan
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Abstract

All biological systems are subject to perturbations: due to thermal fluctuations, external environments, or mutations. Yet, while biological systems are composed of thousands of interacting components, recent high-throughput experiments show that their response to perturbations is surprisingly low-dimensional: confined to only a few stereotyped changes out of the many possible. Here, we explore a unifying dynamical systems framework - soft modes - to explain and analyze low-dimensionality in biology, from molecules to eco-systems. We argue that this one framework of soft modes makes non-trivial 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.

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Christopher Joel Russo, Kabir Husain, Arvind Murugan. 2024-12-18. Soft Modes as a Predictive Framework for Low Dimensional Biological Systems across Scales. https://doi.org/10.1146/annurev-biophys-081624-030543

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