부산대학교 도서관

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 and can be considered as definitions of biological functions shaped by collective intelligence. 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. Author summary: The long-standing effort for annotating protein functions from published experimental evidences is still far from being completed, partly due to a limited number of biocurators involved in it. Wikipedia was thought to be a suitable platform for the protein function curation crowdsourcing through exploiting the wisdom of the crowd principle. Starting from 2008, English Wikipedia was automatically populated with thousands of protein pages and links between them (Gene Wiki project), which created a useful and rapidly evolving knowledge resource. However, it remains unclear what is the benefit of hyperlinking protein pages with the whole Wikipedia knowledge corpus. We applied the recently introduced network analysis method, called reduced Google Matrix (REGOMAX), in order to study the structure of direct and indirect (hidden) links between protein pages through the rest of the global Wikipedia network. As expected, the network of direct links had node degree distribution approximately following the power law. In contrast, the network of hidden links was characterized by larger than expected tight communities of proteins related to their known functions, such as involvement in immune system. The "friendship network" of these protein groups can be used for automated annotations of their functions from non-protein Wikipedia pages. We estimated the size of the expert Wikipedia contributor community, specifically working on protein and associated pages, to be nearly 1000 wikipedians with primarily biomedical background. We conclude that the structure of global Wikipedia network can improve the annotation of protein functions by amplifying the wisdom of the crowd effect. [ABSTRACT FROM AUTHOR]