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Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment

Overview of attention for article published in PLOS ONE, March 2012
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4 news outlets
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13 blogs
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39 X users
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2 Wikipedia pages
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Citations

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292 Mendeley
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14 CiteULike
Title
Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
Published in
PLOS ONE, March 2012
DOI 10.1371/journal.pone.0031362
Pubmed ID
Authors

Alexander Kawrykow, Gary Roumanis, Alfred Kam, Daniel Kwak, Clarence Leung, Chu Wu, Eleyine Zarour, Luis Sarmenta, Mathieu Blanchette, Jérôme Waldispühl

Abstract

Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server.

X Demographics

X Demographics

The data shown below were collected from the profiles of 39 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 292 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 17 6%
Germany 5 2%
United Kingdom 4 1%
France 3 1%
Canada 3 1%
Brazil 2 <1%
Spain 2 <1%
Switzerland 2 <1%
Finland 1 <1%
Other 6 2%
Unknown 247 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 66 23%
Student > Ph. D. Student 65 22%
Student > Master 37 13%
Student > Bachelor 23 8%
Other 20 7%
Other 44 15%
Unknown 37 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 88 30%
Computer Science 53 18%
Social Sciences 19 7%
Environmental Science 14 5%
Biochemistry, Genetics and Molecular Biology 12 4%
Other 62 21%
Unknown 44 15%