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

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Structural information content of networks : Graph entropy based on local vertex functionals. / Dehmer, Matthias; Emmert-Streib, Frank.

julkaisussa: Computational Biology and Chemistry, Vuosikerta 32, Nro 2, 04.2008, s. 131-138.

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Dehmer, Matthias ; Emmert-Streib, Frank. / Structural information content of networks : Graph entropy based on local vertex functionals. Julkaisussa: Computational Biology and Chemistry. 2008 ; Vuosikerta 32, Nro 2. Sivut 131-138.

Bibtex - Lataa

@article{ad28eaf9a47b4861880861fde58767ea,
title = "Structural information content of networks: Graph entropy based on local vertex functionals",
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",
author = "Matthias Dehmer and Frank Emmert-Streib",
year = "2008",
month = "4",
doi = "10.1016/j.compbiolchem.2007.09.007",
language = "English",
volume = "32",
pages = "131--138",
journal = "Computational Biology and Chemistry",
issn = "1476-9271",
publisher = "Elsevier",
number = "2",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Structural information content of networks

T2 - Graph entropy based on local vertex functionals

AU - Dehmer, Matthias

AU - Emmert-Streib, Frank

PY - 2008/4

Y1 - 2008/4

N2 - 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.

AB - 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.

KW - Chemical graph theory

KW - Gene networks

KW - Graph entropy

KW - Information theory

KW - Structural information content

U2 - 10.1016/j.compbiolchem.2007.09.007

DO - 10.1016/j.compbiolchem.2007.09.007

M3 - Article

VL - 32

SP - 131

EP - 138

JO - Computational Biology and Chemistry

JF - Computational Biology and Chemistry

SN - 1476-9271

IS - 2

ER -