Cargando…

Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment

BACKGROUND: 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Kawrykow, Alexander, Roumanis, Gary, Kam, Alfred, Kwak, Daniel, Leung, Clarence, Wu, Chu, Zarour, Eleyine, Sarmenta, Luis, Blanchette, Mathieu, Waldispühl, Jérôme
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296692/
https://www.ncbi.nlm.nih.gov/pubmed/22412834
http://dx.doi.org/10.1371/journal.pone.0031362
_version_ 1782225776337223680
author Kawrykow, Alexander
Roumanis, Gary
Kam, Alfred
Kwak, Daniel
Leung, Clarence
Wu, Chu
Zarour, Eleyine
Sarmenta, Luis
Blanchette, Mathieu
Waldispühl, Jérôme
author_facet Kawrykow, Alexander
Roumanis, Gary
Kam, Alfred
Kwak, Daniel
Leung, Clarence
Wu, Chu
Zarour, Eleyine
Sarmenta, Luis
Blanchette, Mathieu
Waldispühl, Jérôme
author_sort Kawrykow, Alexander
collection PubMed
description BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: We introduce Phylo, a human-based computing framework applying “crowd sourcing” techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. CONCLUSIONS/SIGNIFICANCE: We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of “human-brain peta-flops” of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca.
format Online
Article
Text
id pubmed-3296692
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-32966922012-03-12 Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment Kawrykow, Alexander Roumanis, Gary Kam, Alfred Kwak, Daniel Leung, Clarence Wu, Chu Zarour, Eleyine Sarmenta, Luis Blanchette, Mathieu Waldispühl, Jérôme PLoS One Research Article BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: We introduce Phylo, a human-based computing framework applying “crowd sourcing” techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. CONCLUSIONS/SIGNIFICANCE: We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of “human-brain peta-flops” of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca. Public Library of Science 2012-03-07 /pmc/articles/PMC3296692/ /pubmed/22412834 http://dx.doi.org/10.1371/journal.pone.0031362 Text en Kawrykow et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kawrykow, Alexander
Roumanis, Gary
Kam, Alfred
Kwak, Daniel
Leung, Clarence
Wu, Chu
Zarour, Eleyine
Sarmenta, Luis
Blanchette, Mathieu
Waldispühl, Jérôme
Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title_full Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title_fullStr Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title_full_unstemmed Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title_short Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
title_sort phylo: a citizen science approach for improving multiple sequence alignment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296692/
https://www.ncbi.nlm.nih.gov/pubmed/22412834
http://dx.doi.org/10.1371/journal.pone.0031362
work_keys_str_mv AT kawrykowalexander phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT roumanisgary phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT kamalfred phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT kwakdaniel phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT leungclarence phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT wuchu phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT zaroureleyine phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT sarmentaluis phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT blanchettemathieu phyloacitizenscienceapproachforimprovingmultiplesequencealignment
AT waldispuhljerome phyloacitizenscienceapproachforimprovingmultiplesequencealignment