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计算机辅助结构解析中的图自同构感知算法

Graph automorphism perception algorithms in computer-enhanced structure elucidation.

作者信息

Razinger M, Balasubramanian K, Munk M E

机构信息

Department of Chemistry, Arizona State University, Tempe 85287-1604.

出版信息

J Chem Inf Comput Sci. 1993 Mar-Apr;33(2):197-201. doi: 10.1021/ci00012a003.

DOI:10.1021/ci00012a003
PMID:8314927
Abstract

The concept of graph symmetry is explained in terms of the vertex automorphism group, which is a subgroup of the complete vertex permutation group. The automorphism group can be deduced from the automorphism partition of graph vertices. An algorithm is described which constructs the automorphism group of a graph from the automorphism vertex partitioning. The algorithm is useful especially for graphs which contain more than one vertex-partition set. Several well-known topological symmetry perception algorithms that yield automorphism partitions are compared. The comparison is favorable to the Shelley-Munk algorithm, developed in the framework of the SESAMI system for computer-enhanced structure elucidation.

摘要

图对称性的概念是根据顶点自同构群来解释的,顶点自同构群是完全顶点置换群的一个子群。自同构群可以从图顶点的自同构划分推导出来。描述了一种从自同构顶点划分构建图自同构群的算法。该算法对于包含多个顶点划分集的图特别有用。比较了几种产生自同构划分的著名拓扑对称感知算法。比较结果表明Shelley-Munk算法更具优势,该算法是在用于计算机辅助结构解析的SESAMI系统框架下开发的。

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