How does a cell maintain function despite disruptions to its internal components? What happens when not just one, but two or three genes are knocked out at the same time? This project explores how large-scale genetic interaction data - generated from systematic single, double, and triple gene knockouts in single celled organisms can reveal the internal "logic" of cellular function.
Using datasets from recent high-throughput experiments, we aim to understand how different proteins and pathways compensate for one another, work together, or fail together. These patterns can help us map how the cell is organized, how it prioritizes certain functions, and how complex systems maintain robustness despite perturbations.
Students will work with real experimental datasets to identify patterns, model interactions, and propose rules that describe how cells make decisions under stress or disruption. This project blends data analysis, systems thinking, and biological insight. No prior knowledge of biology or genetics is required.