Menn David, Wang Xiao
School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Methods Mol Biol. 2019;1975:173-189. doi: 10.1007/978-1-4939-9224-9_8.
Stem cells are unique in their ability to differentiate into diverse phenotypes capable of displaying radically different, yet stable, gene expression profiles. Understanding this multistable behavior is key to rationally influencing stem cell differentiation for both research and therapeutic purposes. To this end, mathematical paradigms have been adopted to simulate and explain the dynamics of complex gene networks. In this chapter, we introduce strategies for building deterministic and stochastic mathematical models of gene expression and demonstrate how analysis of these models can benefit our understanding of complex observed behaviors. Developing a mathematical understanding of biological processes is of utmost importance in understanding and controlling stem cell behavior.
干细胞的独特之处在于其能够分化为多种表型,这些表型能够展现出截然不同但却稳定的基因表达谱。理解这种多稳态行为是合理影响干细胞分化以用于研究和治疗目的的关键。为此,已采用数学范式来模拟和解释复杂基因网络的动态变化。在本章中,我们介绍构建基因表达的确定性和随机性数学模型的策略,并展示对这些模型的分析如何有助于我们理解观察到的复杂行为。从数学角度理解生物过程对于理解和控制干细胞行为至关重要。