Title |
Open-Phylo: a customizable crowd-computing platform for multiple sequence alignment
|
---|---|
Published in |
Genome Biology, December 2013
|
DOI | 10.1186/gb-2013-14-10-r116 |
Pubmed ID | |
Authors |
Daniel Kwak, Alfred Kam, David Becerra, Qikuan Zhou, Adam Hops, Eleyine Zarour, Arthur Kam, Luis Sarmenta, Mathieu Blanchette, Jérôme Waldispühl |
Abstract |
Citizen science games such as Galaxy Zoo, Foldit, and Phylo aim to harness the intelligence and processing power generated by crowds of online gamers to solve scientific problems. However, the selection of the data to be analyzed through these games is under the exclusive control of the game designers, and so are the results produced by gamers. Here, we introduce Open-Phylo, a freely accessible crowd-computing platform that enables any scientist to enter our system and use crowds of gamers to assist computer programs in solving one of the most fundamental problems in genomics: the multiple sequence alignment problem. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 24% |
United Kingdom | 6 | 12% |
Canada | 5 | 10% |
France | 1 | 2% |
Switzerland | 1 | 2% |
Sweden | 1 | 2% |
Mexico | 1 | 2% |
Australia | 1 | 2% |
China | 1 | 2% |
Other | 3 | 6% |
Unknown | 17 | 35% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 31 | 63% |
Scientists | 14 | 29% |
Science communicators (journalists, bloggers, editors) | 3 | 6% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 5% |
United Kingdom | 4 | 5% |
Netherlands | 2 | 2% |
Brazil | 1 | 1% |
Sweden | 1 | 1% |
France | 1 | 1% |
Finland | 1 | 1% |
Japan | 1 | 1% |
Peru | 1 | 1% |
Other | 0 | 0% |
Unknown | 71 | 82% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 23 | 26% |
Student > Ph. D. Student | 14 | 16% |
Student > Master | 10 | 11% |
Student > Bachelor | 10 | 11% |
Other | 7 | 8% |
Other | 16 | 18% |
Unknown | 7 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 31 | 36% |
Computer Science | 19 | 22% |
Biochemistry, Genetics and Molecular Biology | 6 | 7% |
Social Sciences | 3 | 3% |
Environmental Science | 3 | 3% |
Other | 14 | 16% |
Unknown | 11 | 13% |