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在复杂生物网络中用最小介质实现目标可控性。

Target controllability with minimal mediators in complex biological networks.

机构信息

Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.

School of Mathematics and Computer Science, University of Tehran, Tehran, Iran.

出版信息

Genomics. 2020 Nov;112(6):4938-4944. doi: 10.1016/j.ygeno.2020.09.003. Epub 2020 Sep 6.

Abstract

Controllability of a complex network system is related to finding a set of minimum number of nodes, known as drivers, controlling which allows having a full control on the dynamics of the network. For some applications, only a portion of the network is required to be controlled, for which target control has been proposed. Often, along the controlling route from driver nodes to target nodes, some mediators (intermediate nodes) are also unwillingly controlled, which might cause various side effects. In controlling cancerous cells, unwillingly controlling healthy cells, might result in weakening them, thus affecting the immune system against cancer. This manuscript proposes a suitable candidate solution to the problem of finding minimum number of driver nodes under minimal mediators. Although many others have attempted to develop algorithms to find minimum number of drivers for target control, the newly proposed algorithm is the first one that is capable of achieving this goal and at the same time, keeping the number of the mediators to a minimum. The proposed controllability condition, based on path lengths between node pairs, meets Kalman's controllability rank condition and can be applied on directed networks. Our results show that the path length is a major determinant of in properties of the target control under minimal mediators. As the average path length becomes larger, the ratio of drivers to target nodes decreases and the ratio of mediators to targets increases. The proposed methodology has potential applications in biological networks. The source code of the algorithm and the networks that have been used are available from the following link: https://github.com/LBBSoft/Target-Control-with-Minimal-Mediators.git.

摘要

复杂网络系统的可控性与找到一组最少数量的节点(称为驱动节点)有关,通过控制这些节点可以完全控制网络的动态。对于某些应用,只需要控制网络的一部分,为此提出了目标控制。通常,在从驱动节点到目标节点的控制路径上,一些中间节点(中介)也会被无意控制,这可能会导致各种副作用。在控制癌细胞时,无意中控制健康细胞可能会削弱它们,从而影响免疫系统对癌症的作用。本文针对在最小中介数量下找到最小驱动节点数量的问题提出了一种合适的候选解决方案。尽管许多人尝试开发用于目标控制的最小驱动节点数量的算法,但新提出的算法是第一个能够实现这一目标的算法,同时还将中介数量保持在最低水平。基于节点对之间路径长度的可控性条件满足卡尔曼可控性秩条件,并且可以应用于有向网络。我们的结果表明,路径长度是最小中介目标控制下的主要决定因素。随着平均路径长度的增加,驱动节点与目标节点的比例减小,而中介节点与目标节点的比例增加。该方法具有在生物网络中应用的潜力。该算法的源代码和已使用的网络可从以下链接获取:https://github.com/LBBSoft/Target-Control-with-Minimal-Mediators.git。

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