Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network

View ORCID ProfileAndrei Zinovyev, View ORCID ProfileUrszula Czerwinska, View ORCID ProfileLaura Cantini, View ORCID ProfileEmmanuel Barillot, View ORCID ProfileKlaus M. Frahm, View ORCID ProfileDima L. Shepelyansky
doi: https://doi.org/10.1101/618447
Andrei Zinovyev
1Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrei Zinovyev
  • For correspondence: andrei.zinovyev@curie.fr
Urszula Czerwinska
1Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Urszula Czerwinska
Laura Cantini
1Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France
2Computational Systems Biology Team, Institut de Biologie de l’Ecole Normale Supérieure, CNRS UMR8197, INSERM U1024, Ecole Normale Supérieure, Paris Sciences et Lettres Research University, 75005 Paris, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Laura Cantini
Emmanuel Barillot
1Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Emmanuel Barillot
Klaus M. Frahm
3Laboratoire de Physique Théorique, IRSAMC, Université de Toulouse, CNRS, UPS, 31062 Toulouse, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Klaus M. Frahm
Dima L. Shepelyansky
3Laboratoire de Physique Théorique, IRSAMC, Université de Toulouse, CNRS, UPS, 31062 Toulouse, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Dima L. Shepelyansky
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

English Wikipedia, containing more than five millions articles, has approximately eleven thousands web pages devoted to proteins or genes most of which were generated by the Gene Wiki project. These pages contain information about interactions between proteins and their functional relationships. At the same time, they are interconnected with other Wikipedia pages describing biological functions, diseases, drugs and other topics curated by independent, not coordinated collective efforts. Therefore, Wikipedia contains a directed network of protein functional relations or physical interactions embedded into the global network of the encyclopedia terms, which defines hidden (indirect) functional proximity between proteins. We applied the recently developed reduced Google Matrix (REGOMAX) algorithm in order to extract the network of hidden functional connections between proteins in Wikipedia. In this network we discovered tight communities which reflect areas of interest in molecular biology or medicine. Moreover, by comparing two snapshots of Wikipedia graph (from years 2013 and 2017), we studied the evolution of the network of direct and hidden protein connections. We concluded that the hidden connections are more dynamic compared to the direct ones and that the size of the hidden interaction communities grows with time. We recapitulate the results of Wikipedia protein community analysis and annotation in the form of an interactive online map, which can serve as a portal to the Gene Wiki project.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted April 25, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network
Andrei Zinovyev, Urszula Czerwinska, Laura Cantini, Emmanuel Barillot, Klaus M. Frahm, Dima L. Shepelyansky
bioRxiv 618447; doi: https://doi.org/10.1101/618447
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network
Andrei Zinovyev, Urszula Czerwinska, Laura Cantini, Emmanuel Barillot, Klaus M. Frahm, Dima L. Shepelyansky
bioRxiv 618447; doi: https://doi.org/10.1101/618447

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4235)
  • Biochemistry (9136)
  • Bioengineering (6784)
  • Bioinformatics (24001)
  • Biophysics (12129)
  • Cancer Biology (9534)
  • Cell Biology (13778)
  • Clinical Trials (138)
  • Developmental Biology (7636)
  • Ecology (11702)
  • Epidemiology (2066)
  • Evolutionary Biology (15513)
  • Genetics (10644)
  • Genomics (14326)
  • Immunology (9483)
  • Microbiology (22840)
  • Molecular Biology (9090)
  • Neuroscience (48995)
  • Paleontology (355)
  • Pathology (1482)
  • Pharmacology and Toxicology (2570)
  • Physiology (3846)
  • Plant Biology (8331)
  • Scientific Communication and Education (1471)
  • Synthetic Biology (2296)
  • Systems Biology (6192)
  • Zoology (1301)