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.
| Original language | English |
|---|---|
| Pages (from-to) | 131-138 |
| Number of pages | 8 |
| Journal | Computational Biology and Chemistry |
| Volume | 32 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Apr 2008 |
| Externally published | Yes |
| Publication type | A1 Journal article-refereed |
Keywords
- Chemical graph theory
- Gene networks
- Graph entropy
- Information theory
- Structural information content
ASJC Scopus subject areas
- Biochemistry
- Structural Biology
- Analytical Chemistry
- Physical and Theoretical Chemistry