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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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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. |
format | Online Article Text |
id | pubmed-8044439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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