Whole cell models (WCMs) use theory and simulation to capture an ever-increasing set of processes and functions exhibited by natural cells. These computer-based, or in silico, cells provide a platform for eventually understanding how a holistic agent emerges from many distinct yet coupled processes. The WCMs developed to date are primarily chemical-kinetics models that accurately represent chemical reaction rates but don't explicitly account for physical processes and how they vary in space and time. This grant provides ongoing support to Roseanna Zia, a Professor of Mechanical Engineering at the University of Missouri, for efforts to develop and expand a whole cell model that explicitly tracks biomolecules and their interactions as they diffuse through a crowded cell interior. Zia’s efforts focus on understanding ribogenesis, the process by which cells build the molecular complexes (ribosomes) responsible for protein synthesis. Zia will develop complex machine learning tools that can simulate in a computationally tractable way the complex process of ribosome formation, and then validate these tools, both against experimental data and against existing simulations that require more computational resources. Zia will leverage these computational tools to expand her model to better understand and simulate important elements of ribogenesis, such as the compaction of rRNA strands into folded, functional configurations and how this folding is affected by intra-cellular conditions like pH, cellular crowding, and protein abundance. These improvements, if successful, will allow Zia’s augmented WCM to simulate about half of ribosome synthesis, and would represent substantial progress towards the ultimate goal of modeling in silico the construction of a full ribosome.