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Transittability of complex networks and its applications to regulatory biomolecular networks

机译:复杂网络的可传递性及其在调控生物分子网络中的应用

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摘要

We have often observed unexpected state transitions of complex systems. We are thus interested in how to steer a complex system from an unexpected state to a desired state. Here we introduce the concept of transittability of complex networks, and derive a new sufficient and necessary condition for state transittability which can be efficiently verified. We define the steering kernel as a minimal set of steering nodes to which control signals must directly be applied for transition between two specific states of a network, and propose a graph-theoretic algorithm to identify the steering kernel of a network for transition between two specific states. We applied our algorithm to 27 real complex networks, finding that sizes of steering kernels required for transittability are much less than those for complete controllability. Furthermore, applications to regulatory biomolecular networks not only validated our method but also identified the steering kernel for their phenotype transitions.
机译:我们经常观察到复杂系统的意外状态转换。因此,我们对如何将复杂系统从意外状态引导到期望状态感兴趣。在这里,我们介绍了复杂网络的可传递性的概念,并为状态可传递性导出了一个新的充要条件,可以有效地对其进行验证。我们将转向核定义为必须直接向其施加控制信号以在网络的两个特定状态之间进行转换的最小转向节点集合,并提出一种图论算法来识别网络的转向核以在两个特定状态之间进行转换状态。我们将算法应用于27个实际的复杂网络,发现可传输性所需的操纵核大小远小于完全可控制性的操纵核大小。此外,在调节性生物分子网络中的应用不仅验证了我们的方法,而且还确定了其表型转变的操纵核心。

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