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Global network identification from reconstructed dynamical structure subnetworks: Applications to biochemical reaction networks

机译:从重构的动力学结构子网络进行全局网络识别:在生化反应网络中的应用

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In this paper we consider the problem of network reconstruction, with applications to biochemical reaction networks. We consider the problem of global network reconstruction when there are a limited number of sensors that can be used to simultaneously measure state information. We introduce dynamical structure functions as a way to formulate the network reconstruction problem and motivate their usage with an example physical system from synthetic biology. In particular, we argue that in synthetic biology research, network verification is paramount to robust circuit operation and thus, network reconstruction is an invaluable tool. Nonetheless, we argue that existing approaches for reconstruction are hampered by limited numbers of biological sensors with high temporal resolution. In this way, we motivate the global network reconstruction problem using partial network information and prove that by performing a series of reconstruction experiments, where each experiment reconstructs a subnetwork dynamical structure function, the global dynamical structure function can be recovered under certain conditions. We illustrate these reconstruction techniques on a recently developed four gene biocircuit, an event detector, used for implementing temporal logic.
机译:在本文中,我们考虑了网络重建的问题,并将其应用于生化反应网络。当可用于同时测量状态信息的传感器数量有限时,我们将考虑全局网络重构的问题。我们介绍了动态结构功能,以此来阐述网络重构问题并通过合成生物学中的示例物理系统激励它们的使用。特别是,我们认为,在合成生物学研究中,网络验证对于稳健的电路操作至关重要,因此,网络重建是一种宝贵的工具。但是,我们认为现有的重建方法受到有限数量的具有高时间分辨率的生物传感器的阻碍。这样,我们利用部分网络信息激发了全球网络的重构问题,并证明了通过执行一系列的重构实验,其中每个实验都重构了子网的动态结构函数,可以在一定条件下恢复全局的动态结构函数。我们在最近开发的四基因生物电路(事件检测器)上说明了这些重建技术,该电路用于实现时态逻辑。

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