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生物网络中临界性的结构决定因素。

Structural determinants of criticality in biological networks.

作者信息

Valverde Sergi, Ohse Sebastian, Turalska Malgorzata, West Bruce J, Garcia-Ojalvo Jordi

机构信息

ICREA-Complex Systems Lab, Universitat Pompeu Fabra Barcelona, Spain ; Institute of Evolutionary Biology (CSIC-UPF), Universitat Pompeu Fabra Barcelona, Spain.

Institute of Molecular Medicine and Cell Research, Albert-Ludwigs-Universität Freiburg Freiburg, Germany.

出版信息

Front Physiol. 2015 May 8;6:127. doi: 10.3389/fphys.2015.00127. eCollection 2015.

Abstract

Many adaptive evolutionary systems display spatial and temporal features, such as long-range correlations, typically associated with the critical point of a phase transition in statistical physics. Empirical and theoretical studies suggest that operating near criticality enhances the functionality of biological networks, such as brain and gene networks, in terms for instance of information processing, robustness, and evolvability. While previous studies have explained criticality with specific system features, we still lack a general theory of critical behavior in biological systems. Here we look at this problem from the complex systems perspective, since in principle all critical biological circuits have in common the fact that their internal organization can be described as a complex network. An important question is how self-similar structure influences self-similar dynamics. Modularity and heterogeneity, for instance, affect the location of critical points and can be used to tune the system toward criticality. We review and discuss recent studies on the criticality of neuronal and genetic networks, and discuss the implications of network theory when assessing the evolutionary features of criticality.

摘要

许多适应性进化系统呈现出空间和时间特征,例如长程相关性,这通常与统计物理学中相变的临界点相关联。实证和理论研究表明,在临界状态附近运行可增强生物网络(如大脑和基因网络)在信息处理、稳健性和可进化性等方面的功能。虽然先前的研究已用特定系统特征解释了临界性,但我们仍缺乏关于生物系统临界行为的通用理论。在此,我们从复杂系统的角度审视这个问题,因为原则上所有临界生物回路都有一个共同之处,即其内部组织可被描述为一个复杂网络。一个重要问题是自相似结构如何影响自相似动力学。例如,模块化和异质性会影响临界点的位置,并可用于将系统调整至临界状态。我们回顾并讨论了近期关于神经元网络和遗传网络临界性的研究,并在评估临界性的进化特征时讨论了网络理论的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a75/4424853/1d988cc90f9b/fphys-06-00127-g0001.jpg

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