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Prize-based contests can provide solutions to computational biology problems

Prize-based contests can provide solutions to computational biology problems

Nature Biotechnology volume 31pages 108–111 (2013)Cite this article

To the Editor

Advances in biotechnology have fueled the generation of unprecedented quantities of data across the life sciences. However, finding analysts who can address such 'big data' problems effectively has become a significant research bottleneck. Historically, prize-based contests have had striking success in attracting unconventional individuals who can overcome difficult challenges. To determine whether this approach could solve a real big-data biologic algorithm problem, we used a complex immunogenomics problem as the basis for a two-week online contest broadcast to participants outside academia and biomedical disciplines. Participants in our contest produced over 600 submissions containing 89 novel computational approaches to the problem. Thirty submissions exceeded the benchmark performance of the US National Institutes of Health's MegaBLAST. The best achieved both greater accuracy and speed (1,000 times greater). Here we show the potential of using online prize-based contests to access individuals without domain-specific backgrounds to address big-data challenges in the life sciences.

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Acknowledgements

Harvard Business School's Division of Research and Faculty Development funded the prize money and supported K.R.L., E.L., C.B. and A.M. K.R.L. and K.J.B. were also supported by the NASA Tournament Lab, which is funded by the NASA Human Exploration and Operations Mission Directorate. E.C.G. was supported by the Harvard Clinical and Translational Science Center (NCRR 5UL1RR025758 and 5UL1RR025758-S), and R.A.A. was supported by the Klarman Family Foundation. P.-R.L. was supported by US National Defense Science and Engineeering and US National Science Foundation graduate research fellowships.

Author information Author notes
  1. Karim R Lakhani, Kevin J Boudreau, Ramy A Arnaout and Eva C Guinan: These authors contributed equally.

Authors and Affiliations
  1. Harvard Business School, Boston, Massachusetts, USA

    Karim R Lakhani, Carliss Baldwin, Eric Lonstein & Alan MacCormack

  2. Harvard-NASA Tournament Lab, Institute for Quantitative Social Science,

    Karim R Lakhani & Kevin J Boudreau

  3. London Business School, London, UK

    Kevin J Boudreau

  4. Department of Mathematics and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Po-Ru Loh

  5. TopCoder.com, Glastonbury, Connecticut, USA

    Lars Backstrom & Mike Lydon

  6. Department of Pathology and Division of Clinical Informatics, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

    Ramy A Arnaout

  7. Harvard Medical School, Boston, Massachusetts, USA

    Ramy A Arnaout & Eva C Guinan

  8. Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Eva C Guinan

Authors
  1. Karim R Lakhani
  2. Kevin J Boudreau
  3. Po-Ru Loh
  4. Lars Backstrom
  5. Carliss Baldwin
  6. Eric Lonstein
  7. Mike Lydon
  8. Alan MacCormack
  9. Ramy A Arnaout
  10. Eva C Guinan
Corresponding author

Correspondence to Eva C Guinan.

Ethics declarations Competing interests

M.L. is employed by TopCoder.com. L.B. was a paid consultant to TopCoder.com at the time the contest was designed and executed.

Supplementary information About this article Cite this article

Lakhani, K., Boudreau, K., Loh, PR. et al. Prize-based contests can provide solutions to computational biology problems. Nat Biotechnol 31, 108–111 (2013). https://doi.org/10.1038/nbt.2495

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