Networks are everywhere in biology and medicine. Genes interact through intricate regulatory circuits to drive cellular function. The human microbiome—a key player in our health and well-being—is shaped by a dynamic web of microbial interactions. Even our thoughts and behaviors emerge from the collective activity of vast neuronal networks in the brain.

At the Orr Lab, we explore the fundamental principles that govern these complex, interdependent networks of networks. Our research seeks to understand how structure and dynamics interact in biological systems—and how this interplay shapes function, resilience, and failure at the system level.

We use tools from statistical physics, nonlinear dynamics, and graph theory—such as percolation theory and dynamical modeling—to investigate real-world biological networks. By integrating these approaches with machine learning and high-dimensional biological data, we aim to uncover universal principles that explain how complex systems operate—and how they break down in disease and aging.