Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease, is a progressive and ultimately fatal neurodegenerative disease affecting 1 in 400 people in which the motor neurons die. There is only one approved treatment but no shortage of clinical trials. Read More.
Using data from old clinical trials, two groups of researchers have found a better way to predict how amyotrophic lateral sclerosis (ALS) progresses in different patients. Read more
A joint blog post discussing Google Cloud’s involvement in the DREAM Somatic Mutation Calling Challenge. Read more
Andrew Lash at Xconomy discusses a variety of efforts to better understand Alzheimer’s Disease, including the DREAM AD#1 Challenge. Read more
A study published June 1 in the journal Nature Biotechnology describes the results of an open challenge to predict which breast cancer cell lines will respond to which drugs, based only on the sum of cells’ genomic data. Read more
Competition to develop more efficient treatment strategies for breast cancer patients awards six leading teams cash prizes. Read full article
Global CEO Initiative on Alzheimer’s Disease Announces a Big Data Challenge to Find New Predictors of Cognitive Decline. Full article here.
Canadian and US Leaders in Cancer Research Announce a Big Data Challenge to Develop Robust Methodologies for Predicting Cancer Mutations. Full article here.
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