Learning Rules of Epithelial Tissue Dynamics

Faculty Mentors: Margaret Gardel (University of Chicago), Cara J. Gottardi (Northwestern University), & Vincenzo Vitelli (University of Chicago)

This project seeks to decode how molecular networks govern dynamic behaviors across subcellular, cellular, and multicellular scales, a process critical for development, physiological homeostasis, and disease progression. Using epithelial tissue as a highly tractable model system, the researchers are developing advanced machine learning architectures—specifically an approach called “GraphWaveNet”—to capture the stochastic dynamics of biological data defined on graphs. By integrating physical principles with multi-omics data, the team aims to create a general-purpose computational toolset for “coarse-graining” tissue dynamics. Ultimately, this framework will enable predictive modeling of living systems, offering new insights into biological adaptation and potential therapeutic interventions.