All living organisms rely on interacting networks of genes to carry out vital functions like growth, development, and response to the environment. These networks must operate reliably even in the face of unpredictable changes, such as random mutations or environmental shifts. One key to that stability is a biological concept called canalization. This project investigates how gene regulatory networks (GRNs) achieve such stability by studying how their structure shapes their behavior. Using simple but powerful mathematical models, the research will uncover underlying design principles that make these networks robust. To achieve this, the project will analyze hundreds of previously published expert-curated GRN models using new computational tools and theoretical insights. The findings will be validated through biological experiments in a model plant species, Arabidopsis. The broader impacts of this project include the creation of public databases and software tools that will allow scientists to explore how gene networks function. By involving students in all aspects of the research, this project contributes to the interdisciplinary training of the STEM workforce. Moreover, this project has the potential to support efforts in agriculture, biology and medicine by helping scientists better understand how genetic systems function and maintain their resilience. This project seeks to elucidate design principles of GRNs using discrete dynamical systems, specifically Boolean and