School of Mathematics and Statistics, Henan University, Kaifeng 475001, China.
School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China.
Int J Mol Sci. 2024 Sep 23;25(18):10204. doi: 10.3390/ijms251810204.
The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data.
丝裂原活化蛋白激酶(MAPK)通路是一个重要的细胞内信号级联反应,在各种细胞过程中起着关键作用。理解该通路的调节机制对于开发相关疾病的有效干预措施和靶向治疗至关重要。单细胞蛋白质组学技术的最新进展为研究不同细胞和细胞类型中复杂多信号网络内的异质性和噪声提供了前所未有的机会。数学建模已成为一个强大的跨学科工具,连接了数学和实验生物学,为这些复杂的细胞过程提供了有价值的见解。此外,还开发了统计方法来推断通路拓扑结构并估计动态模型中的未知参数。本综述全面分析了 MAPK 通路的数学建模如何加深我们对其调节机制的理解,增强对系统行为的预测,并为实验研究提供信息,特别关注使用单细胞蛋白质组学数据进行建模和推断的最新进展。