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Wikipedia network analysis of cancer interactions and world influence

We apply the Google matrix algorithms for analysis of interactions and influence of 37 cancer types, 203 cancer drugs and 195 world countries using the network of 5 416 537 English Wikipedia articles with all their directed hyperlinks. The PageRank algorithm provides a ranking of cancers which has 6...

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Detalles Bibliográficos
Autores principales: Rollin, Guillaume, Lages, José, Shepelyansky, Dima L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752824/
https://www.ncbi.nlm.nih.gov/pubmed/31536541
http://dx.doi.org/10.1371/journal.pone.0222508
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author Rollin, Guillaume
Lages, José
Shepelyansky, Dima L.
author_facet Rollin, Guillaume
Lages, José
Shepelyansky, Dima L.
author_sort Rollin, Guillaume
collection PubMed
description We apply the Google matrix algorithms for analysis of interactions and influence of 37 cancer types, 203 cancer drugs and 195 world countries using the network of 5 416 537 English Wikipedia articles with all their directed hyperlinks. The PageRank algorithm provides a ranking of cancers which has 60% and 70% overlaps with the top 10 deadliest cancers extracted from World Health Organization GLOBOCAN 2018 and Global Burden of Diseases Study 2017, respectively. The recently developed reduced Google matrix algorithm gives networks of interactions between cancers, drugs and countries taking into account all direct and indirect links between these selected 435 entities. These reduced networks allow to obtain sensitivity of countries to specific cancers and drugs. The strongest links between cancers and drugs are in good agreement with the approved medical prescriptions of specific drugs to specific cancers. We argue that this analysis of knowledge accumulated in Wikipedia provides useful complementary global information about interdependencies between cancers, drugs and world countries.
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spelling pubmed-67528242019-09-27 Wikipedia network analysis of cancer interactions and world influence Rollin, Guillaume Lages, José Shepelyansky, Dima L. PLoS One Research Article We apply the Google matrix algorithms for analysis of interactions and influence of 37 cancer types, 203 cancer drugs and 195 world countries using the network of 5 416 537 English Wikipedia articles with all their directed hyperlinks. The PageRank algorithm provides a ranking of cancers which has 60% and 70% overlaps with the top 10 deadliest cancers extracted from World Health Organization GLOBOCAN 2018 and Global Burden of Diseases Study 2017, respectively. The recently developed reduced Google matrix algorithm gives networks of interactions between cancers, drugs and countries taking into account all direct and indirect links between these selected 435 entities. These reduced networks allow to obtain sensitivity of countries to specific cancers and drugs. The strongest links between cancers and drugs are in good agreement with the approved medical prescriptions of specific drugs to specific cancers. We argue that this analysis of knowledge accumulated in Wikipedia provides useful complementary global information about interdependencies between cancers, drugs and world countries. Public Library of Science 2019-09-19 /pmc/articles/PMC6752824/ /pubmed/31536541 http://dx.doi.org/10.1371/journal.pone.0222508 Text en © 2019 Rollin 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rollin, Guillaume
Lages, José
Shepelyansky, Dima L.
Wikipedia network analysis of cancer interactions and world influence
title Wikipedia network analysis of cancer interactions and world influence
title_full Wikipedia network analysis of cancer interactions and world influence
title_fullStr Wikipedia network analysis of cancer interactions and world influence
title_full_unstemmed Wikipedia network analysis of cancer interactions and world influence
title_short Wikipedia network analysis of cancer interactions and world influence
title_sort wikipedia network analysis of cancer interactions and world influence
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752824/
https://www.ncbi.nlm.nih.gov/pubmed/31536541
http://dx.doi.org/10.1371/journal.pone.0222508
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