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Application of Multilayer Network Models in Bioinformatics

Multilayer networks provide an efficient tool for studying complex systems, and with current, dramatic development of bioinformatics tools and accumulation of data, researchers have applied network concepts to all aspects of research problems in the field of biology. Addressing the combination of mu...

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Detalles Bibliográficos
Autores principales: Lv, Yuanyuan, Huang, Shan, Zhang, Tianjiao, Gao, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044439/
https://www.ncbi.nlm.nih.gov/pubmed/33868392
http://dx.doi.org/10.3389/fgene.2021.664860
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author Lv, Yuanyuan
Huang, Shan
Zhang, Tianjiao
Gao, Bo
author_facet Lv, Yuanyuan
Huang, Shan
Zhang, Tianjiao
Gao, Bo
author_sort Lv, Yuanyuan
collection PubMed
description Multilayer networks provide an efficient tool for studying complex systems, and with current, dramatic development of bioinformatics tools and accumulation of data, researchers have applied network concepts to all aspects of research problems in the field of biology. Addressing the combination of multilayer networks and bioinformatics, through summarizing the applications of multilayer network models in bioinformatics, this review classifies applications and presents a summary of the latest results. Among them, we classify the applications of multilayer networks according to the object of study. Furthermore, because of the systemic nature of biology, we classify the subjects into several hierarchical categories, such as cells, tissues, organs, and groups, according to the hierarchical nature of biological composition. On the basis of the complexity of biological systems, we selected brain research for a detailed explanation. We describe the application of multilayer networks and chronological networks in brain research to demonstrate the primary ideas associated with the application of multilayer networks in biological studies. Finally, we mention a quality assessment method focusing on multilayer and single-layer networks as an evaluation method emphasizing network studies.
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spelling pubmed-80444392021-04-15 Application of Multilayer Network Models in Bioinformatics Lv, Yuanyuan Huang, Shan Zhang, Tianjiao Gao, Bo Front Genet Genetics Multilayer networks provide an efficient tool for studying complex systems, and with current, dramatic development of bioinformatics tools and accumulation of data, researchers have applied network concepts to all aspects of research problems in the field of biology. Addressing the combination of multilayer networks and bioinformatics, through summarizing the applications of multilayer network models in bioinformatics, this review classifies applications and presents a summary of the latest results. Among them, we classify the applications of multilayer networks according to the object of study. Furthermore, because of the systemic nature of biology, we classify the subjects into several hierarchical categories, such as cells, tissues, organs, and groups, according to the hierarchical nature of biological composition. On the basis of the complexity of biological systems, we selected brain research for a detailed explanation. We describe the application of multilayer networks and chronological networks in brain research to demonstrate the primary ideas associated with the application of multilayer networks in biological studies. Finally, we mention a quality assessment method focusing on multilayer and single-layer networks as an evaluation method emphasizing network studies. Frontiers Media S.A. 2021-03-31 /pmc/articles/PMC8044439/ /pubmed/33868392 http://dx.doi.org/10.3389/fgene.2021.664860 Text en Copyright © 2021 Lv, Huang, Zhang and Gao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Lv, Yuanyuan
Huang, Shan
Zhang, Tianjiao
Gao, Bo
Application of Multilayer Network Models in Bioinformatics
title Application of Multilayer Network Models in Bioinformatics
title_full Application of Multilayer Network Models in Bioinformatics
title_fullStr Application of Multilayer Network Models in Bioinformatics
title_full_unstemmed Application of Multilayer Network Models in Bioinformatics
title_short Application of Multilayer Network Models in Bioinformatics
title_sort application of multilayer network models in bioinformatics
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044439/
https://www.ncbi.nlm.nih.gov/pubmed/33868392
http://dx.doi.org/10.3389/fgene.2021.664860
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