...
We are pleased to announce that the DREAM8 Challenges listed below opened for participation on June 10, 2013 and will continue until are now open for participation. During the "Challenge season" spanning from June 10 to September 15, 2013, Sage Bionetworks and DREAM will run the three Challenges described below. Best performers in the DREAM8 Challenges will be invited to present at the DREAM conference (November 8-12, Toronto, Canada) with travel expenses covered by the Sage/DREAM organizers. Sage Bionetworks and DREAM are also working with high impact journals to ensure that the methodology developed by the Challenges' best performers will be considered for publication under the Challenge-assisted Peer Review format.
...
We will provide genetics and transcriptomics information of the 1000 Genomes Project (www.1000genomes.org), as well as cytotoxicity measures derived from compound exposure to over a hundred toxic agents using the 1000 genomes lymphoblastoid cell lines. Participants are tasked with solving two related subchallenges: (1) developing develop predictive models of cytotoxicity using genetic and genomic data to predict individual responses to compound exposure and (2) using use chemical attributes to predict population-based cytotoxicity characteristics (median, variance) for unknown a set of compounds.
The Whole-Cell Parameter Estimation DREAM Challenge
Participants will be provided with a whole cell model of Mycoplasma genitalium and tasked with estimating the model parameters from simulated data for specific biological processes from simulated data. The simulated data to be provided represents possible measurements in actual experiments: participants will will have a credit budget and will be able to purchase this simulated data on demand with the aim to refine the parameters under estimation.
About DREAM Challenges
Sage Bionetworks and DREAM are convinced that running open computational Challenges focused on important unsolved questions in systems biomedicine can help advance basic and translational science. By presenting the research community with well-formulated questions that usually involve complex data, we effectively enable the sharing and improvement of predictive models, accelerating many-fold the analysis of such data. The ultimate goal, beyond the competitive aspect of these Challenges, is to foster collaborations of like-minded researchers that together will find the solution for vexing problems that matter most to citizens and patients.
...