We continue to build on our computational innovations to both quantify and predict local and global cardiac geometry changes resulting from hemodynamic and/or genetic changes. We advance computational modeling strategies that accommodate growth within fluid and tissue mechanical fields. This requires unique fluid-structure interaction, constitutive theory, and geometry/mesh adaptation innovations. We further add to our discrete models biological elements such as cells, soluble chemicals, and extracellular matrix proteins in a grid of cellular nodes that can proliferate, move, and/or apoptose. Each cell also contains a molecular systems network that incorporates known signaling pathways that will define how it responds to external molecular and mechanical stimuli. We will predict cross-pathway bottlenecks in valvulogenic signaling that are intractable experimentally or through sequencing data alone. We utilize statistical distribution models to reduce parameter variables to their minimum essential sets, while preserving our capacity for prediction of emergent phenomena. We can directly test these predictions via our unique in vitro and in vivo experimental systems. These approaches enable us to identify master regulators of development that act across multiple signaling networks and biological scales.