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Structural information content of networks: Graph entropy based on local vertex functionals

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)131-138
Number of pages8
JournalComputational Biology and Chemistry
Volume32
Issue number2
DOIs
Publication statusPublished - Apr 2008
Externally publishedYes
Publication typeA1 Journal article-refereed

Abstract

In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating j-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties.

Keywords

  • Chemical graph theory, Gene networks, Graph entropy, Information theory, Structural information content