The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Crowdsourcing biomedical research: leveraging communities as innovation engines
Open accessAbstract
The generation of large-scale biomedical data is creating unprecedented opportunities for basic and translational science. Typically, the data producers perform initial analyses, but it is very likely that the most informative methods may reside with other groups. Crowdsourcing the analysis of complex and massive data has emerged as a framework to find robust methodologies. When the crowdsourcing is done in the form of collaborative scientific competitions, known as Challenges, the validation of the methods is inherently addressed. Challenges also encourage open innovation, create collaborative communities to solve diverse and important biomedical problems, and foster the creation and dissemination of well-curated data repositories.
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Cites
The cancer genome atlas pan-cancer analysis project
The Cancer Genome Atlas Research Network, Weinstein, J. N., Collisson, E. A., Mills, G. B., Shaw, K. R. M., Ozenberger, B. A., Ellrott, K., Shmulevich, I., Sander, C., & Stuart, J. M. (2013) · Nature Genetics · doi:10.1038/ng.2764 · Cited by 9,092
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
International network of cancer genome projects
The International Cancer Genome Consortium (2010) · Nature · doi:10.1038/nature08987 · Cited by 2,299
Data collection in a flat world: the strengths and weaknesses of Mechanical Turk samples
Goodman, J. K., Cryder, C. E., & Cheema, A. (2013) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1753 · Cited by 2,242 · cited 1×
“The Mechanical Turk approach provides an online workforce that allows people to complete work, or ‘human intelligence tasks’, in exchange for a small amount of money 67 .”
BackgroundPredicting 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
Big Data: Astronomical or Genomical?
Stephens, Z. D., Lee, S. Y., Faghri, F., Campbell, R. H., Zhai, C., Efron, M. J., Iyer, R., Schatz, M. C., Sinha, S., & Robinson, G. E. (2015) · PLOS Biology · doi:10.1371/journal.pbio.1002195 · Cited by 1,340
A community-driven global reconstruction of human metabolism
Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2488 · Cited by 1,019
CAPRI: A Critical Assessment of PRedicted Interactions
Janin, J., Henrick, K., Moult, J., Eyck, L. T., Sternberg, M. J. E., Vajda, S., Vakser, I., & Wodak, S. J. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10381 · Cited by 703
Assessment of transcript reconstruction methods for RNA-seq
The RGASP Consortium, Steijger, T., Abril, J. F., Engström, P. G., Kokocinski, F., Hubbard, T. J., Guigó, R., Harrow, J., & Bertone, P. (2013) · Nature Methods · doi:10.1038/nmeth.2714 · Cited by 699
Cited by
Wells, D. K., van Buuren, M. M., Dang, K. K., Hubbard-Lucey, V. M., Sheehan, K. C. F., Campbell, K. M., Lamb, A., Ward, J. P., Sidney, J., Blazquez, A. B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.015 · Cited by 538
Schaffter, T., Buist, D. S. M., Lee, C. I., Nikulin, Y., Ribli, D., Guan, Y., Lotter, W., Jie, Z., Du, H., Wang, S., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.0265 · Cited by 409
Self-citationMultimodal data fusion for cancer biomarker discovery with deep learning
Steyaert, S., Pizurica, M., Nagaraj, D., Khandelwal, P., Hernandez-Boussard, T., Gentles, A. J., & Gevaert, O. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00633-5 · Cited by 402
Menden, M. P., Wang, D., Mason, M. J., Szalai, B., Bulusu, K. C., Guan, Y., Yu, T., Kang, J., Jeon, M., Wolfinger, R., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09799-2 · Cited by 363
Self-citationMapping of Crowdsourcing in Health: Systematic Review
Créquit, P., Mansouri, G., Benchoufi, M., Vivot, A., & Ravaud, P. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9330 · Cited by 135
Metadata
- Authors
- Saez-Rodriguez, J., Costello, J. C., Friend, S. H., Kellen, M. R., Mangravite, L., Meyer, P., Norman, T., & Stolovitzky, G.
- Venue
- Nature Reviews Genetics
- Published
- 2016-07-15
- Volume
- 17
- Issue
- 8
- Pages
- 470-486
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2475102260
- Cited by
- 165
- References
- 19
- FWCI
- 3.43
- Type
- journal article
- Language
- en
- Open access
- green
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- Saez-Rodriguez, J., Costello, J. C., Friend, S. H., Kellen, M. R., Mangravite, L., Meyer, P., Norman, T., & Stolovitzky, G. (2016). Crowdsourcing biomedical research: leveraging communities as innovation engines. Nature Reviews Genetics. https://doi.org/10.1038/nrg.2016.69
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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