Algorithm discovery by protein folding game players

被引:320
作者
Khatib, Firas [1 ]
Cooper, Seth [2 ]
Tyka, Michael D. [1 ]
Xu, Kefan [2 ]
Makedon, Ilya [2 ]
Popovic, Zoran [2 ]
Baker, David [1 ,3 ]
机构
[1] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[2] Univ Washington, Dept Comp Sci & Engn, Seattle, WA 98195 USA
[3] Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
基金
美国国家科学基金会;
关键词
citizen science; crowd-sourcing; optimization; structure prediction; strategy;
D O I
10.1073/pnas.1115898108
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.
引用
收藏
页码:18949 / 18953
页数:5
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