| Title |
WeFold: A coopetition for protein structure prediction
|
|---|---|
| Published in |
Proteins: Structure, Function, and Bioinformatics, July 2014
|
| DOI | 10.1002/prot.24538 |
| Pubmed ID | |
| Authors |
George A. Khoury, Adam Liwo, Firas Khatib, Hongyi Zhou, Gaurav Chopra, Jaume Bacardit, Leandro O. Bortot, Rodrigo A. Faccioli, Xin Deng, Yi He, Pawel Krupa, Jilong Li, Magdalena A. Mozolewska, Adam K. Sieradzan, James Smadbeck, Tomasz Wirecki, Seth Cooper, Jeff Flatten, Kefan Xu, David Baker, Jianlin Cheng, Alexandre C. B. Delbem, Christodoulos A. Floudas, Chen Keasar, Michael Levitt, Zoran Popović, Harold A. Scheraga, Jeffrey Skolnick, Silvia N. Crivelli, Foldit Players |
| Abstract |
The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 31% |
| United Kingdom | 3 | 19% |
| Australia | 2 | 13% |
| Japan | 1 | 6% |
| Unknown | 5 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 81% |
| Scientists | 3 | 19% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Singapore | 1 | <1% |
| Japan | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Czechia | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 111 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 24% |
| Researcher | 26 | 22% |
| Student > Master | 12 | 10% |
| Professor | 9 | 8% |
| Professor > Associate Professor | 8 | 7% |
| Other | 22 | 19% |
| Unknown | 12 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 20% |
| Biochemistry, Genetics and Molecular Biology | 17 | 15% |
| Computer Science | 16 | 14% |
| Business, Management and Accounting | 8 | 7% |
| Chemistry | 8 | 7% |
| Other | 30 | 26% |
| Unknown | 15 | 13% |