henhaobio
Sign in

PLoS Computational BiologySystems BiologyPeer-reviewed journal article

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

Andrei Y. ZinovyeviD, Urszula CzerwińskaiD, Laura CantiniiD, Emmanuel BarillotiD, Klaus M. FrahmiD, Dima L. ShepelyanskyiD

PDFDOIPreprint

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.

Citations
4
FWCI
0.32
Field percentile
48th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISAnderson '25Kotelnikova '22Dilucca '21Cheung '21Frahm '20Rameshwari '18
59% semantic matchSystems Biology
Oliver Faulkner Anderson, Altaf Barelvi, Aden O'Brien+3 more·PLoS ONE·Sep 5, 2025