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Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks
Biological systems are composed of highly complex networks, and decoding the functional significance of individual network components is critical for understanding healthy and diseased states. Several algorithms have been designed to identify the most influential regulatory points within a network....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660386/ https://www.ncbi.nlm.nih.gov/pubmed/33205118 http://dx.doi.org/10.1016/j.patter.2020.100052 |
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author | Salavaty, Abbas Ramialison, Mirana Currie, Peter D. |
author_facet | Salavaty, Abbas Ramialison, Mirana Currie, Peter D. |
author_sort | Salavaty, Abbas |
collection | PubMed |
description | Biological systems are composed of highly complex networks, and decoding the functional significance of individual network components is critical for understanding healthy and diseased states. Several algorithms have been designed to identify the most influential regulatory points within a network. However, current methods do not address all the topological dimensions of a network or correct for inherent positional biases, which limits their applicability. To overcome this computational deficit, we undertook a statistical assessment of 200 real-world and simulated networks to decipher associations between centrality measures and developed an algorithm termed Integrated Value of Influence (IVI), which integrates the most important and commonly used network centrality measures in an unbiased way. When compared against 12 other contemporary influential node identification methods on ten different networks, the IVI algorithm outperformed all other assessed methods. Using this versatile method, network researchers can now identify the most influential network nodes. |
format | Online Article Text |
id | pubmed-7660386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-76603862020-11-16 Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks Salavaty, Abbas Ramialison, Mirana Currie, Peter D. Patterns (N Y) Article Biological systems are composed of highly complex networks, and decoding the functional significance of individual network components is critical for understanding healthy and diseased states. Several algorithms have been designed to identify the most influential regulatory points within a network. However, current methods do not address all the topological dimensions of a network or correct for inherent positional biases, which limits their applicability. To overcome this computational deficit, we undertook a statistical assessment of 200 real-world and simulated networks to decipher associations between centrality measures and developed an algorithm termed Integrated Value of Influence (IVI), which integrates the most important and commonly used network centrality measures in an unbiased way. When compared against 12 other contemporary influential node identification methods on ten different networks, the IVI algorithm outperformed all other assessed methods. Using this versatile method, network researchers can now identify the most influential network nodes. Elsevier 2020-06-22 /pmc/articles/PMC7660386/ /pubmed/33205118 http://dx.doi.org/10.1016/j.patter.2020.100052 Text en © 2020 The Authors 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 Salavaty, Abbas Ramialison, Mirana Currie, Peter D. Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title | Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title_full | Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title_fullStr | Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title_full_unstemmed | Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title_short | Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks |
title_sort | integrated value of influence: an integrative method for the identification of the most influential nodes within networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660386/ https://www.ncbi.nlm.nih.gov/pubmed/33205118 http://dx.doi.org/10.1016/j.patter.2020.100052 |
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