Computational Biology: Biophysical Modeling

About

Our group studies the dynamics of complex and active materials, as well as aspects of collective behavior and self-organization in both natural and synthetic systems.

Examples are the organization and dynamics of the nucleus, the structure and assembly of spindles, the positioning and transport of cellular organelles, and fluid-structure problems in biology.

With a focus on complex biophysical systems that arise in cell biology, our research includes the assembly, structure, positioning and transport of cellular organelles such as the spindle, the organization and dynamics of the nucleus, biophysical fluid-structure problems, and related self-organizing active matter systems. We develop both the theoretical models and the software needed for large-scale dynamics simulation of continuum and many-body biophysics problems.

Observation

We begin by gathering high-quality data through experiments, performed either in-house at the CCBScope Observatory or by our collaborators. This step is critical for identifying patterns, proposing hypotheses, and pinpointing the key constituents driving the biological phenomenon.

Large-Scale Simulation

Using state-of-the-art computational tools and high-performance computing resources, we translate our observations into detailed simulations. These allow us to explore complex, multi-scale phenomena with biologically-relevant particle numbers.

Reduced Order Modeling

Insights from microscopic simulations are distilled into coarse-grained models that encapsulate the core mechanisms of the systems under investigation. These models strike a balance between complexity and interpretability, enabling robust predictions and theoretical advancements.

Analysis

We rigorously analyze both simulations and models to uncover new insights, identify critical parameters, and validate results against experiments. The latter often involves advanced statistical methods, machine learning techniques, and collaboration with domain experts.

By studying how specific biological systems function and developing appropriate methods, we often gain insights into broader biological and physical principles.