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EVE Online players further scientific research using pattern-matching minigame

EVE Online players taking part in developer CCP Games' 'Citizen Science' project have helped scientists broaden their understanding of protein patterns within human cells.

Chris Kerr, News Editor

August 22, 2018

2 Min Read
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EVE Online players taking part in developer CCP Games' 'Citizen Science' project have helped scientists broaden their understanding of protein patterns within human cells. 

The project began back in March 2016, when CCP partnered with various research groups to create a pattern-matching minigame called Project Discovery.

The game asked players to match images of protein patterns pulled from a database of over 13 million human cells, with CCP offering a variety of in-game rewards to incentivize participation. 

Over two years later the EVE community has delivered the goods, and those scientists involved in the project say they've now developed a more granular understanding of protein patterns thanks to player efforts.

"EVE players helped boost the artificial intelligence system used for predicting protein localization on a subcellular level," explains a CCP press release.

"That combination of crowdsourcing and AI led to improved classification of subcellular protein patterns and the first-time identification of ten new members of the family of cellular structures known as 'Rods & Rings'."

The data amassed by players is now being fed into the publicly-available Human Protein Atlas database, and will become a resource for researchers around the world. 

KTH Royal Institute of Technology researcher Professor Emma Lundburg has suggested the Citizen Science initiative will be the first of many projects to unite video games and science to further real-world progress through play. 

"I believe that the integration of scientific tasks into established computer games will be a commonly used approach in the future to harness the brain processing power of humans," she commented.

"The intricate designs of citizen science games feeding directly into machine learning models has the power to rapidly leverage the output of large-scale science efforts. We are grateful to all the citizen scientists who participated in this project, and for the discoveries they made."

About the Author

Chris Kerr

News Editor, GameDeveloper.com

Game Developer news editor Chris Kerr is an award-winning journalist and reporter with over a decade of experience in the game industry. His byline has appeared in notable print and digital publications including Edge, Stuff, Wireframe, International Business Times, and PocketGamer.biz. Throughout his career, Chris has covered major industry events including GDC, PAX Australia, Gamescom, Paris Games Week, and Develop Brighton. He has featured on the judging panel at The Develop Star Awards on multiple occasions and appeared on BBC Radio 5 Live to discuss breaking news.

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