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Predicting protein structures with a multiplayer online game

Author

Listed:
  • Seth Cooper

    (University of Washington, Box 352350, Seattle, Washington 98195, USA)

  • Firas Khatib

    (University of Washington, Box 357350, Seattle, Washington 98195, USA)

  • Adrien Treuille

    (University of Washington, Box 352350, Seattle, Washington 98195, USA
    School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, USA)

  • Janos Barbero

    (University of Washington, Box 352350, Seattle, Washington 98195, USA)

  • Jeehyung Lee

    (School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, USA)

  • Michael Beenen

    (University of Washington, Box 352350, Seattle, Washington 98195, USA)

  • Andrew Leaver-Fay

    (University of Washington, Box 357350, Seattle, Washington 98195, USA
    Present address: Department of Biochemistry, University of North Carolina, CB 7260, Chapel Hill, North Carolina 27599, USA.)

  • David Baker

    (University of Washington, Box 357350, Seattle, Washington 98195, USA
    Howard Hughes Medical Institute, University of Washington, Box 357370, Seattle, Washington 98195, USA)

  • Zoran Popović

    (University of Washington, Box 352350, Seattle, Washington 98195, USA)

  • Foldit players

Abstract

Many hands make light work A natural polypeptide chain can fold into a native protein in microseconds, but predicting such stable three-dimensional structure from any given amino-acid sequence and first physical principles remains a formidable computational challenge. Aiming to recruit human visual and strategic powers to the task, Seth Cooper, David Baker and colleagues turned their 'Rosetta' structure-prediction algorithm into an online multiplayer game called Foldit, in which thousands of non-scientists competed and collaborated to produce a rich set of new algorithms and search strategies for protein structure refinement. The work shows that even computationally complex scientific problems can be effectively crowd-sourced using interactive multiplayer games.

Suggested Citation

  • Seth Cooper & Firas Khatib & Adrien Treuille & Janos Barbero & Jeehyung Lee & Michael Beenen & Andrew Leaver-Fay & David Baker & Zoran Popović & Foldit players, 2010. "Predicting protein structures with a multiplayer online game," Nature, Nature, vol. 466(7307), pages 756-760, August.
    • Handle: RePEc:nat:nature:v:466:y:2010:i:7307:d:10.1038_nature09304
    DOI: 10.1038/nature09304
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    Cited by:

    1. Spartaco Albertarelli & Piero Fraternali & Sergio Herrera & Mark Melenhorst & Jasminko Novak & Chiara Pasini & Andrea-Emilio Rizzoli & Cristina Rottondi, 2018. "A Survey on the Design of Gamified Systems for Energy and Water Sustainability," Games, MDPI, vol. 9(3), pages 1-34, June.
    2. Sherwani, Y & Ahmed, M & Muntasir, M & El-Hilly, A & Iqbal, S & Siddiqui, S & Al-Fagih, Z & Usmani, O & Eisingerich, AB, 2015. "Examining the role of gamification and use of mHealth apps in the context of smoking cessation: A review of extant knowledge and outlook," Working Papers 25458, Imperial College, London, Imperial College Business School.
    3. Vito D’Orazio & Michael Kenwick & Matthew Lane & Glenn Palmer & David Reitter, 2016. "Crowdsourcing the Measurement of Interstate Conflict," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-21, June.
    4. Maryam Lotfian & Jens Ingensand & Maria Antonia Brovelli, 2021. "The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    5. Joanna Chataway & Sarah Parks & Elta Smith, 2017. "How Will Open Science Impact on University-Industry Collaboration?," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 11(2), pages 44-53.
    6. Ayat Abourashed & Laura Doornekamp & Santi Escartin & Constantianus J. M. Koenraadt & Maarten Schrama & Marlies Wagener & Frederic Bartumeus & Eric C. M. van Gorp, 2021. "The Potential Role of School Citizen Science Programs in Infectious Disease Surveillance: A Critical Review," IJERPH, MDPI, vol. 18(13), pages 1-18, June.
    7. Yury Kryvasheyeu & Haohui Chen & Esteban Moro & Pascal Van Hentenryck & Manuel Cebrian, 2015. "Performance of Social Network Sensors during Hurricane Sandy," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
    8. Christoph Safferling & Aaron Lowen, 2011. "Economics in the Kingdom of Loathing: Analysis of Virtual Market Data," Working Paper Series of the Department of Economics, University of Konstanz 2011-30, Department of Economics, University of Konstanz.
    9. Prpić, John & Shukla, Prashant P. & Kietzmann, Jan H. & McCarthy, Ian P., 2015. "How to work a crowd: Developing crowd capital through crowdsourcing," Business Horizons, Elsevier, vol. 58(1), pages 77-85.
    10. Robert Swain & Alex Berger & Josh Bongard & Paul Hines, 2015. "Participation and Contribution in Crowdsourced Surveys," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-21, April.
    11. Naihui Zhou & Zachary D Siegel & Scott Zarecor & Nigel Lee & Darwin A Campbell & Carson M Andorf & Dan Nettleton & Carolyn J Lawrence-Dill & Baskar Ganapathysubramanian & Jonathan W Kelly & Iddo Fried, 2018. "Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-16, July.
    12. Jennifer Lewis Priestley & Robert J. McGrath, 2019. "The Evolution of Data Science: A New Mode of Knowledge Production," International Journal of Knowledge Management (IJKM), IGI Global, vol. 15(2), pages 97-109, April.
    13. Kovacs, Attila, 2018. "Gender Differences in Equity Crowdfunding," OSF Preprints 5pcmb, Center for Open Science.
    14. Siluo Yang & Dietmar Wolfram & Feifei Wang, 2017. "The relationship between the author byline and contribution lists: a comparison of three general medical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1273-1296, March.
    15. Prpić, John, 2017. "How To Work A Crowd: Developing Crowd Capital Through Crowdsourcing," SocArXiv jer9k, Center for Open Science.
    16. Jonathan R Karr & Alex H Williams & Jeremy D Zucker & Andreas Raue & Bernhard Steiert & Jens Timmer & Clemens Kreutz & DREAM8 Parameter Estimation Challenge Consortium & Simon Wilkinson & Brandon A Al, 2015. "Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-21, May.
    17. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.
    18. Sam Mavandadi & Stoyan Dimitrov & Steve Feng & Frank Yu & Uzair Sikora & Oguzhan Yaglidere & Swati Padmanabhan & Karin Nielsen & Aydogan Ozcan, 2012. "Distributed Medical Image Analysis and Diagnosis through Crowd-Sourced Games: A Malaria Case Study," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.

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