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Interrelations of Graph Distance Measures Based on Topological Indices

In this paper, we derive interrelations of graph distance measures by means of inequalities. For this investigation we are using graph distance measures based on topological indices that have not been studied in this context. Specifically, we are using the well-known Wiener index, Randić index, eige...

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Detalles Bibliográficos
Autores principales: Dehmer, Matthias, Emmert-Streib, Frank, Shi, Yongtang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3997355/
https://www.ncbi.nlm.nih.gov/pubmed/24759679
http://dx.doi.org/10.1371/journal.pone.0094985
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author Dehmer, Matthias
Emmert-Streib, Frank
Shi, Yongtang
author_facet Dehmer, Matthias
Emmert-Streib, Frank
Shi, Yongtang
author_sort Dehmer, Matthias
collection PubMed
description In this paper, we derive interrelations of graph distance measures by means of inequalities. For this investigation we are using graph distance measures based on topological indices that have not been studied in this context. Specifically, we are using the well-known Wiener index, Randić index, eigenvalue-based quantities and graph entropies. In addition to this analysis, we present results from numerical studies exploring various properties of the measures and aspects of their quality. Our results could find application in chemoinformatics and computational biology where the structural investigation of chemical components and gene networks is currently of great interest.
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spelling pubmed-39973552014-04-29 Interrelations of Graph Distance Measures Based on Topological Indices Dehmer, Matthias Emmert-Streib, Frank Shi, Yongtang PLoS One Research Article In this paper, we derive interrelations of graph distance measures by means of inequalities. For this investigation we are using graph distance measures based on topological indices that have not been studied in this context. Specifically, we are using the well-known Wiener index, Randić index, eigenvalue-based quantities and graph entropies. In addition to this analysis, we present results from numerical studies exploring various properties of the measures and aspects of their quality. Our results could find application in chemoinformatics and computational biology where the structural investigation of chemical components and gene networks is currently of great interest. Public Library of Science 2014-04-23 /pmc/articles/PMC3997355/ /pubmed/24759679 http://dx.doi.org/10.1371/journal.pone.0094985 Text en © 2014 Dehmer et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Dehmer, Matthias
Emmert-Streib, Frank
Shi, Yongtang
Interrelations of Graph Distance Measures Based on Topological Indices
title Interrelations of Graph Distance Measures Based on Topological Indices
title_full Interrelations of Graph Distance Measures Based on Topological Indices
title_fullStr Interrelations of Graph Distance Measures Based on Topological Indices
title_full_unstemmed Interrelations of Graph Distance Measures Based on Topological Indices
title_short Interrelations of Graph Distance Measures Based on Topological Indices
title_sort interrelations of graph distance measures based on topological indices
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3997355/
https://www.ncbi.nlm.nih.gov/pubmed/24759679
http://dx.doi.org/10.1371/journal.pone.0094985
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