Abstract：
Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models used in the literature, considering mathematical frameworks at the molecular, cellular, and system levels. We report key challenges in the field and discuss opportunities for genome-scale models, machine learning, and cybergenetics to expand the capabilities of model-driven mammalian cell biodesign.
摘要：
数学建模在哺乳动物合成生物学中起着至关重要的作用，通过提供一个框架来设计和优化设计电路和工程生物过程，预测他们的行为，并指导实验设计。这里,我们回顾了文献中使用的最新模型，考虑到分子的数学框架，细胞，和系统级别。我们报告了该领域的主要挑战，并讨论了基因组尺度模型的机会，机器学习,和网络遗传学，以扩大模型驱动的哺乳动物细胞生物设计的能力。
