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Study of biological networks using graph theory

As an effective modeling, analysis and computational tool, graph theory is widely used in biological mathematics to deal with various biology problems. In the field of microbiology, graph can express the molecular structure, where cell, gene or protein can be denoted as a vertex, and the connect ele...

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Detalles Bibliográficos
Autores principales: Gao, Wei, Wu, Hualong, Siddiqui, Muhammad Kamran, Baig, Abdul Qudair
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117245/
https://www.ncbi.nlm.nih.gov/pubmed/30174525
http://dx.doi.org/10.1016/j.sjbs.2017.11.022
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author Gao, Wei
Wu, Hualong
Siddiqui, Muhammad Kamran
Baig, Abdul Qudair
author_facet Gao, Wei
Wu, Hualong
Siddiqui, Muhammad Kamran
Baig, Abdul Qudair
author_sort Gao, Wei
collection PubMed
description As an effective modeling, analysis and computational tool, graph theory is widely used in biological mathematics to deal with various biology problems. In the field of microbiology, graph can express the molecular structure, where cell, gene or protein can be denoted as a vertex, and the connect element can be regarded as an edge. In this way, the biological activity characteristic can be measured via topological index computing in the corresponding graphs. In our article, we mainly study the biology features of biological networks in terms of eccentric topological indices computation. By means of graph structure analysis and distance calculating, the exact expression of several important eccentric related indices of hypertree network and X-tree are determined. The conclusions we get in this paper illustrate that the bioengineering has the promising application prospects.
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spelling pubmed-61172452018-08-31 Study of biological networks using graph theory Gao, Wei Wu, Hualong Siddiqui, Muhammad Kamran Baig, Abdul Qudair Saudi J Biol Sci Article As an effective modeling, analysis and computational tool, graph theory is widely used in biological mathematics to deal with various biology problems. In the field of microbiology, graph can express the molecular structure, where cell, gene or protein can be denoted as a vertex, and the connect element can be regarded as an edge. In this way, the biological activity characteristic can be measured via topological index computing in the corresponding graphs. In our article, we mainly study the biology features of biological networks in terms of eccentric topological indices computation. By means of graph structure analysis and distance calculating, the exact expression of several important eccentric related indices of hypertree network and X-tree are determined. The conclusions we get in this paper illustrate that the bioengineering has the promising application prospects. Elsevier 2018-09 2017-11-14 /pmc/articles/PMC6117245/ /pubmed/30174525 http://dx.doi.org/10.1016/j.sjbs.2017.11.022 Text en © 2017 Production and hosting by Elsevier B.V. on behalf of King Saud University. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Gao, Wei
Wu, Hualong
Siddiqui, Muhammad Kamran
Baig, Abdul Qudair
Study of biological networks using graph theory
title Study of biological networks using graph theory
title_full Study of biological networks using graph theory
title_fullStr Study of biological networks using graph theory
title_full_unstemmed Study of biological networks using graph theory
title_short Study of biological networks using graph theory
title_sort study of biological networks using graph theory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117245/
https://www.ncbi.nlm.nih.gov/pubmed/30174525
http://dx.doi.org/10.1016/j.sjbs.2017.11.022
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