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gene folding, crowd sourcing, algorithms, pattern recognition


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Gamers Beat Algorithms at Protein Folding

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully "crowd-sourced" through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space.

Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

Seth Cooper (University of Washington)
Firas Khatib (University of Washington)
Adrien Treuille (Carnegie Mellon)
Janos Barbero (University of Washington)
Jeehyung Lee (University of Washington)
Michael Beenen (University of Washington)
Andrew Leaver-Fay (University of North Carolina)
David Baker (University of Washington)
Zoran Popovic (University of Washington)

Agencies (that have supported the research):
National Science Foundation, the U.S. Defense Advanced Research Projects Agency, the Howard Hughes Medical Institute, Microsoft Corp. and Nvidia Corp


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