Mechanistic interpretation of biological tissue growth experiments with a computational model
This paper presents a computational model that simulates the interplay between geometry, mechanics, and stochasticity in tissue growth to enable the quantitative analysis of morphology and the inference of dynamic growth mechanisms from static experimental data, demonstrated through applications in 3D-printed scaffolds and cortical bone formation.