Sai Bavisetty

Understanding how the structure of a network constrains and drives its dynamics is a central challenge in complex biological systems. While network topology is known to influence phenomena such as multistability, robustness, synchronization, and spreading behavior, the precise mechanisms linking structure to dynamics remain only partially understood. Many real world networks display hallmark properties of complex systems such as feedback loops, modularity, and nonlinear interactions that make it difficult to predict dynamical outcomes from connectivity alone. This minisymposium showcases recent advances aimed at closing this gap. The talks highlight new mathematical and computational approaches that reveal how patterns of interaction shape collective behavior in biological, social, and engineered networks. By integrating theoretical insights with application driven examples, the session seeks to illuminate unifying principles that govern the structure–dynamics relationship and to inspire future work in this rapidly developing area.

The hypothesis that biological systems exhibit a modular structure is widely accepted. Beyond being a “fundamental law of biology,” it has the potential for important applications, for instance in biomedicine and synthetic biology. It could also serve as an organizational principle for the analysis of high-dimensional complex -omics datasets. However, there is currently no widely accepted definition of what comprises a biological “module”. There is also a lack of foundational research on modularity at both the theoretical and applied level. To address this problem, the proposed workshop will bring together an interdisciplinary group of researchers from biology, modeling, mathematics, and fields outside of biology that currently use the modularity concept, such as engineering and computer science.