Adjoint systems for models of cell signaling pathways and their application to parameter fitting
Adjoint systems for models of cell signaling pathways and their application to parameter fitting
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DOI：
10.1109/tcbb.2007.1016
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发表时间：
2007-07-01
影响因子：
4.5
通讯作者：
Swierniak, Andrzej
中科院分区：
文献类型：
--
作者：
Fujarewicz, Krzysztof;Kimmel, Marek;Swierniak, Andrzej
本文研究了细胞信号通路数学模型的拟合问题。这类模型通常采用非线性常微分方程组的形式。虽然模型在时间上是连续的，但在拟合过程中使用的性能指标涉及在离散时刻进行的测量。伴随灵敏度分析是寻找性能指标在模型参数空间中的梯度的工具。本文采用了一种结构形式的伴随灵敏度分析方法--广义时间反向传播(GBPTT)。该方法特别适用于混合、连续-离散时间系统。作为一个例子，我们使用了核因子-kappa B调节模块的数学模型，它在动物的先天免疫反应中发挥着重要作用。
The paper concerns the problem of fitting mathematical models of cell signaling pathways. Such models frequently take the form of sets of nonlinear ordinary differential equations. While the model is continuous in time, the performance index used in the fitting procedure involves measurements taken at discrete time moments. Adjoint sensitivity analysis is a tool which can be used for finding the gradient of a performance index in the space of parameters of the model. In the paper, a structural formulation of adjoint sensitivity analysis called the Generalized Backpropagation Through Time (GBPTT) is used. The method is especially suited for hybrid, continuous-discrete time systems. As an example, we use the mathematical model of the NF-kappa B regulatory module, which plays a major role in the innate immune response in animals.