Observability of complex systems
Observability of complex systems
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DOI：
10.1073/pnas.1215508110
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发表时间：
2013-02-12
影响因子：
11.1
通讯作者：
Barabasi, Albert-Laszlo
中科院分区：
文献类型：
--
作者：
Liu, Yang-Yu;Slotine, Jean-Jacques;Barabasi, Albert-Laszlo
一个复杂系统的定量描述是固有的限制，我们的能力，估计系统的内部状态从实验可访问的输出。虽然所有内部变量的同时测量，如细胞中所有代谢物的浓度，提供了一个完整的描述系统的状态，在实践中，实验访问仅限于一个子集的变量，或传感器。一个系统被称为可观测的，如果我们可以重建系统的完整的内部状态从它的输出。在这里，我们采用了一种图形化的方法，从管理系统的动力学定律，以确定传感器是必要的，以重建一个复杂的系统的完整的内部状态。我们将这种方法应用于生化反应系统，发现所识别的传感器不仅是必要的，而且是足够的可观测性。所开发的方法还可以识别目标或部分可观测性的最佳传感器，帮助我们从适当选择的输出中重建选定的状态变量，这是最佳生物标志物设计的先决条件。考虑到可观测性在复杂系统中的基本作用，这些结果为系统地探索各种自然，技术和社会经济系统的动态提供了途径。
A quantitative description of a complex system is inherently limited by our ability to estimate the system's internal state from experimentally accessible outputs. Although the simultaneous measurement of all internal variables, like all metabolite concentrations in a cell, offers a complete description of a system's state, in practice experimental access is limited to only a subset of variables, or sensors. A system is called observable if we can reconstruct the system's complete internal state from its outputs. Here, we adopt a graphical approach derived from the dynamical laws that govern a system to determine the sensors that are necessary to reconstruct the full internal state of a complex system. We apply this approach to biochemical reaction systems, finding that the identified sensors are not only necessary but also sufficient for observability. The developed approach can also identify the optimal sensors for target or partial observability, helping us reconstruct selected state variables from appropriately chosen outputs, a prerequisite for optimal biomarker design. Given the fundamental role observability plays in complex systems, these results offer avenues to systematically explore the dynamics of a wide range of natural, technological and socioeconomic systems.