Computational challenges are tapping the collective wisdom of the scientific community to solve medicine’s biggest problems. Full article here.
The Breast Cancer’s DREAM challenge (DREAM7) on Science Translation Medicine. See the published articles:
A. A. Margolin, E. Bilal, E. Huang, T. C. Norman, L. Ottestad, B. H. Mecham, B. Sauerwine, M. R. Kellen, L. M. Mangravite, M. D. Furia, H. K. M. Vollan, O. M. Rueda, J. Guinney, N. A. Deflaux, B. Hoff, X. Schildwachter, H. G. Russnes, D. Park, V. O. Vang, T. Pirtle, L. Youseff, C. Citro, C. Curtis, V. N. Kristensen, J. Hellerstein, S. H. Friend, G. Stolovitzky, S. Aparicio, C. Caldas, A.-L. BÃ¸rresen-Dale, Systematic Analysis of Challenge-Driven Improvements in Molecular Prognostic Models for Breast Cancer. Sci. Transl. Med. 5, 181re1 (2013).
W.-Y. Cheng, T.-H. O. Yang, D. Anastassiou, Development of a Prognostic Model for Breast Cancer Survival in an Open Challenge Environment. Sci. Transl. Med. 5, 181ra50 (2013).
Please follow the links to read in different venues about this translational medicine challenge.
Bio-IT-World: Algorithm to Decrease Needed Number of ALS Clinical Trial Patients
Boston.com: Prize4Life taps into global big data expertise to fight Lou Gehrig’s disease
San Francisco Business Times: Stanford team winds $20K for algorithm aimed at Lou Gehrig’s disease drug trials
An interesting discussion in the blog: “21st Century Scientist, Thoughts on modern scientific research“, on the pros and cons of sharing code in collaborative-competitions such as the Sage Bionetworks-DREAM challenge.
Check this link to solve the SAGE/DREAM challenge as a game!