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This content will become publicly available on May 6, 2026

Title: Soft Modes as a Predictive Framework for Low-Dimensional Biological Systems Across Scales
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.  more » « less
Award ID(s):
2317138
PAR ID:
10595345
Author(s) / Creator(s):
; ;
Publisher / Repository:
Annual Reviews
Date Published:
Journal Name:
Annual Review of Biophysics
Volume:
54
Issue:
1
ISSN:
1936-122X
Page Range / eLocation ID:
401 to 426
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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