6533b852fe1ef96bd12ab828
RESEARCH PRODUCT
Wikipedia network analysis of cancer interactions and world influence
José LagesGuillaume RollinDima L. Shepelyanskysubject
PageRankDatabases FactualComputer scienceSocial Sciences01 natural sciencesLung and Intrathoracic TumorsHematologic Cancers and Related Disorders0302 clinical medicineSociologyNeoplasmsBreast TumorsMedicine and Health SciencesComputingMilieux_MISCELLANEOUSNon-Hodgkin lymphoma0303 health sciencesMultidisciplinaryGoogle matrixApplied MathematicsSimulation and ModelingProstate Cancer[PHYS.PHYS.PHYS-SOC-PH]Physics [physics]/Physics [physics]/Physics and Society [physics.soc-ph]QRProstate DiseasesOnline EncyclopediasHematology[SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciencesOvarian CancerOncology030220 oncology & carcinogenesisPhysical SciencesMedicineLymphomasCancersAlgorithmsNetwork analysisResearch ArticleScienceUrologyMEDLINEComplex networksAntineoplastic Agents[SDV.CAN]Life Sciences [q-bio]/CancerResearch and Analysis Methods[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]World Wide Web03 medical and health sciences0103 physical sciencesBreast CancerLeukemiasmedicineHumansMass Media010306 general physicsPagerank algorithm030304 developmental biologyGoogle matrixCancerCancers and NeoplasmsHyperlinkmedicine.diseaseData scienceCommunicationsGenitourinary Tract TumorsCancer drugsRankingEncyclopedias[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]Gynecological TumorsMathematicsWikipediadescription
AbstractWe 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 the importance order of cancers which has 60% and 70% overlaps with the top 10 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-23 |