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Identifiability of population models via a measure theoretical approach

机译:通过测量理论方法的人口模型的可识别性

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Heterogeneity in cell populations is a major factor in the dynamics of cellular systems in living tissue or microbial colonies. This heterogeneity needs to be taken into account for the interpretation of experimental observations as well as in the construction of predictive models for cellular systems. A common modelling framework for heterogeneous cell population is by an infinite ensemble of single cell models. The state of a cell population is in this framework modelled by the distribution of the single cell states. In this paper we study under which conditions the population model is identifiable, i.e., we can determine the initial distribution of cell states and parameters from a dynamic output distribution. We derive a necessary condition on the single cell model based on the classical observability results from linear and nonlinear control theory. Our results are illustrated via examples.
机译:细胞群中的异质性是活组织或微生物菌落中细胞系统动态的主要因素。需要考虑这种异质性以解释实验观察以及蜂窝系统预测模型的构建。异构细胞群的常见建模框架是单细胞模型的无限组合。细胞群的状态在该框架中由单个细胞状态的分布建模。在本文中,我们研究了人口模型的条件是可识别的,即,我们可以从动态输出分布确定单元格状态和参数的初始分布。基于线性和非线性控制理论的经典可观察性导致,我们在单电池模型中获得了必要的条件。我们的结果通过示例说明。

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