Global scale analysis and prediction of human cellular behaviour in a complex environment – GLOBCELL

Establish the global gene expression profile (approximately 40,000 genes) of cells in the presence of multiple stimuli.
Define dominance of each stimulus based on global analysis tools. Analyze the geometry and architecture of this complex data sets.
Analyze the gene-by-gene interactions induced by the multiple stimuli for each of the 40,000 genes. Develop appropriate algorithms and statistical methods. Identify additivity, synergies, inhibition, dominance and emergence.
Model cellular pathways in response to multiple stimuli as compared to individual stimuli. Analyze interaction between pathways by in silico experiments.
Built dynamic models based on kinetics (time-course) data sets. Use these models to predict interactions between cell signaling pathways.
In the end, built predictive tools of the behaviour of a human cell-type in a complex environment that would best reflect physiological or pathological conditions.
Analyze cell behaviour to combinations of drugs as a service to the pharmaceutical industry. Use the models to predict efficacy and toxicity of drugs on human cells.
Identify new therapeutic targets critically involved in cellular responses to inflammatory environments.