MacArthur Ben D, Sánchez-García Rubén J
Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, New York, 10029 New York, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80(2 Pt 2):026117. doi: 10.1103/PhysRevE.80.026117. Epub 2009 Aug 19.
Many real-world complex networks contain a significant amount of structural redundancy, in which multiple vertices play identical topological roles. Such redundancy arises naturally from the simple growth processes which form and shape many real-world systems. Since structurally redundant elements may be permuted without altering network structure, redundancy may be formally investigated by examining network automorphism (symmetry) groups. Here, we use a group-theoretic approach to give a complete description of spectral signatures of redundancy in undirected networks. In particular, we describe how a network's automorphism group may be used to directly associate specific eigenvalues and eigenvectors with specific network motifs.
许多现实世界中的复杂网络都包含大量的结构冗余,其中多个顶点扮演着相同的拓扑角色。这种冗余自然地源于形成和塑造许多现实世界系统的简单增长过程。由于结构冗余元素可以在不改变网络结构的情况下进行置换,因此可以通过研究网络自同构(对称)群来正式研究冗余。在这里,我们使用群论方法对无向网络中冗余的频谱特征进行完整描述。特别是,我们描述了如何使用网络的自同构群将特定的特征值和特征向量与特定的网络基序直接关联起来。