BUILDING BIOLOGICAL INTUITION BY MODELING THE DYNAMICS OF LIVING SYSTEMS
DR. NEDA BAGHERI
Assistant Professor of Chemical and Biological Engineering
Cell population systems present a labyrinth of coupled feedback loops. These networks of loops are embedded within and among decentralized modules to enable tightly regulated, and inherently robust, cellular responses. To both understand and redirect these responses, we need to uncover the fundamental rules of cellular language. Computational models are essential tools that can be used to guide such biological intuition. In this talk I highlight how we harness machine learning and agent-based models to help explain biological observations and to elucidate design principles that drive both individual cellular decisions and cell populations. I am particularly interested in uncovering the multiscale nature of cellular signaling—how “the whole is greater than the sum of its parts”—and in predicting cell population dynamics from the composition of simpler biological modules. In piecing together the language of cell signaling, we step closer to predicting, and subsequently controlling, rich complex biological function.