The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
Open accessAbstract
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.
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Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
Predicting protein structures with a multiplayer online game
Cooper, S., Khatib, F., Treuille, A., Barbero, J., Lee, J., Beenen, M., Leaver-Fay, A., Baker, D., Popović, Z., & players, F. (2010) · Nature · doi:10.1038/nature09304 · Cited by 1,368
LAGAN and Multi-LAGAN: Efficient tools for large-scale multiple alignment of genomic DNA
Brudno, M., Do, C. B., Cooper, G. M., Kim, M. F., Davydov, E., Program, N. C. S., Green, E. D., Sidow, A., & Batzoglou, S. (2003) · Genome Research · doi:10.1101/gr.926603 · Cited by 1,115
A high-resolution map of human evolutionary constraint using 29 mammals
Broad Institute Sequencing Platform and Whole Genome Assembly Team, Lindblad-Toh, K., Baylor College of Medicine Human Genome Sequencing Center Sequencing Team, Genome Institute at Washington University, Garber, M., Zuk, O., Lin, M. F., Parker, B. J., Washietl, S., Kheradpour, P., et al. (2011) · Nature · doi:10.1038/nature10530 · Cited by 1,108
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Lv, Z., Tek, A., Da Silva, F., Empereur-mot, C., Chavent, M., & Baaden, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057990 · Cited by 309
Understanding Human-Machine Networks: A Cross-Disciplinary Survey
Tsvetkova, M., Yasseri, T., Meyer, E. T., Pickering, J. B., Engen, V., Walland, P., Lüders, M., Følstad, A., & Bravos, G. (2018) · ACM Computing Surveys · doi:10.1145/3039868 · Cited by 67
Improving microbial phylogeny with citizen science within a mass-market video game
Sarrazin-Gendron, R., Ghasemloo Gheidari, P., Butyaev, A., Keding, T., Cai, E., Zheng, J., Mutalova, R., Mounthanyvong, J., Zhu, Y., Nazarova, E., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02175-6 · Cited by 9
Self-citationPlaying the System: Can Puzzle Players Teach us How to Solve Hard Problems?
Mutalova, R., Sarrazin-Gendron, R., Cai, E., Richard, G., Ghasemloo Gheidari, P., Caisse, S., Knight, R., Blanchette, M., Szantner, A., & Waldispühl, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581375 · Cited by 6
Self-citationPlayer-Guided AI outperforms standard AI in Sequence Alignment Puzzles
Mutalova, R., Sarrazin-Gendron, R., Ghasemloo Gheidari, P., Cai, E., Richard, G., Caisse, S., Knight, R., Blanchette, M., Szantner, A., & Waldispühl, J. (2023) · Proceedings of The ACM Collective Intelligence Conference · doi:10.1145/3582269.3615597 · Cited by 1
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Metadata
- Authors
- Kawrykow, A., Roumanis, G., Kam, A., Kwak, D., Leung, C., Wu, C., Zarour, E., players, P., Sarmenta, L., Blanchette, M., & Waldispühl, J.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-03-07
- Volume
- 7
- Issue
- 3
- Pages
- e31362
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2051741744
- Cited by
- 234
- References
- 4
- FWCI
- 8.48
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kawrykow, A., Roumanis, G., Kam, A., Kwak, D., Leung, C., Wu, C., Zarour, E., players, P., Sarmenta, L., Blanchette, M., & Waldispühl, J. (2012). Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment. PLoS ONE. https://doi.org/10.1371/journal.pone.0031362
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