October 2, 2014
  • Building communities to advance science

DREAM Challenges pose fundamental questions about systems biology and translational medicine. Designed and run by a community of researchers from a variety of organizations, our challenges invite participants to propose solutions — fostering collaboration and building communities in the process. Expertise and institutional support are provided by Sage Bionetworks, along with the infrastructure to host challenges via their Synapse platform. Together, we share a vision allowing individuals and groups to collaborate openly so that the  “wisdom of the crowd” provides the greatest impact on science and human health.
Sage

FEATURED PUBLICATION

Keller A, Gerkin R, et. al.  Predicting human olfactory perception from chemical features of odor molecules; Science; 24 Feb 2017; Vol 355; Issue 6327;  820-826; DOI: 10.1126/science.aai2014  

FEATURED CONTENT

The DREAM Challenge team discuss what DREAM Means to them in this new DREAM Challenges Video produced at the 2016 conference in Phoenix.  

CHALLENGE RESULTS

DREAM 10 – ALS Stratification Prize4Life Challenge

Final results available. »more

DREAM 9.5 Prostate Cancer DREAM Challenge

Final results available. »more

DREAM 9.5 -DREAM Olfaction Prediction Challenge

Final results available. »more  
March 31, 2017

Advantages of a Truly Open-Access Data-Sharing Model

Multi-institutional randomized clinical trials have been a feature of oncology research in the United States since the 1950s. Since that time, cancer-treatment trials have been continuously funded by the National Cancer Institute (NCI) through a program that has evolved to become the National Clinical Trials Network (NCTN). Currently, approximately 19,000 patients with cancer participate in NCTN clinical trials each year. Approximately 70,000 additional patients with cancer are enrolled each year in treatment trials sponsored by the pharmaceutical industry (Read more.)

March 17, 2017

Predicting smell from structure

Algorithms can predict a molecule’s odour on the basis of its chemical structure.

Pablo Meyer at IBM’s Computational Biology Center in Yorktown Heights, New York, and his colleagues, asked 49 people to smell hundreds of molecules (pictured) and rate them on intensity, pleasantness and 19 other descriptors, such as ‘fruit’, ‘musky’ and ‘bakery’. (Read More)

March 8, 2017

Artificial intelligence grows a nose

Predicting color is easy: Shine a light with a wavelength of 510 nanometers, and most people will say it looks green. Yet figuring out exactly how a particular molecule will smell is much tougher. Now, 22 teams of computer scientists have unveiled a set of algorithms able to predict the odor of different molecules based on their chemical structure. It remains to be seen how broadly useful such programs will be, but one hope is that such algorithms may help fragrancemakers and food producers design new odorants with precisely tailored scents. (Read more)