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To that end, the DREAM consortium will leverage is leveraging the genetics and transcriptomics information of the 1000 genomes project Genomes Project (1000genomes.org), as well as cytotoxicity measures derived from compound exposure to over a hundred toxic agents using the 1000 genomes lymphoblastoid cell lines. Challenge Participants are tasked with solving two related subchallenges: (1) developing predictive models of cytotoxicity using genetic and genomic data to predict individual responses to compound exposure and (2) using chemical attributes to predict population-based cytotoxicity characteristics (median, variance) for unknown compounds.
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The Whole-Cell Parameter Estimation DREAM Challenge
The goal of the Whole Cell Parameter Estimation Challenge is to use crowd-sourcing to determine the ability of the computational systems biology community to infer the kinetic parameters underlying biological processes.
The challenge Challenge consists of predicting a subset of the kinetic parameters used in a recently published whole-cell model of Mycoplasma genitalium. Participants are tasked with estimating the model parameters from simulated data (representing possible measurements in actual experiments) purchased on demand and chosen with the aim to refine the parameters under estimation.
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