Quantitative Immunology by Data Analysis Using Mathematical Models
Quantitative Immunology by Data Analysis Using Mathematical Models
复制标题
DOI：
10.1016/b978-0-12-809633-8.20250-1
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
S. Iwanami;S. Iwami
中科院分区：
文献类型：
--
作者：
S. Iwanami;S. Iwami
数学模型可以描述细胞或抗原之间的相互作用，已广泛应用于免疫学实验数据的分析。许多数学建模研究为免疫系统提供了新的见解。这些研究采用了生态学或人口学中常用的基于种群动力学的广义数学模型。通过讨论细胞分化、淋巴细胞周转和病毒动力学的几个研究，我们证明了广义数学模型对免疫学数据分析的适用性。
Mathematical models have been widely used for analysis of experimental data in immunology, which can describe the interactions among cells or antigens. Many mathematical modeling studies have provided novel insights into immune systems. These researches adopt a generalized mathematical model based on population dynamics, which is frequently used in ecology or demography. By discussing several studies of cell differentiation, lymphocyte turnover and virus dynamics, we demonstrate the applicability of the generalized mathematical model to immunology data analysis.