New mathematical approaches to learn the equations of life from noisy data

必须不断开发新的数学模型和数学建模方法来解释新兴的生物技术实验。当代组织工程学的研究包括在3D打印支架上种植组织，以模拟体内受限的几何形状。以前的组织生长数学模型主要集中在计算昂贵的离散数学模型上，这些模型不太适合参数推断和实验设计。该项目将提供和部署高保真、计算高效的移动边界连续统数学模型，这些模型将：(I)预测/解释新的实验，(Ii)提供对生物机制的定量洞察，以及(Iii)实现可重复的实验设计。

New mathematical models and mathematical modelling methods must be continually developed to interpret emerging biotechnology experiments. Contemporary research in tissue engineering involves growing tissues on 3d-printed scaffolds to mimic constrained in vivo geometries. Previous mathematical models of tissue growth focus on computationally expensive discrete mathematical models that are poorly suited for parameter inference and experimental design. This project will deliver and deploy high-fidelity, computationally efficient moving boundary continuum mathematical models that will: (i) predict/interpret new experiments, (ii) provide quantitative insight into biological mechanisms, and (iii) enable reproducible experimental design.