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INTEGRATION OF THE SYSTEM MODELS OF INSULIN SIGNAL.. (MITIN)
INTEGRATION OF THE SYSTEM MODELS OF INSULIN SIGNALLING AND OF MITOCHONDRIAL FUNCTION AND ITS APPLICATION IN THE STUDY OF COMPLEX DISEASES
(MITIN)
Date du début: 1 nov. 2008,
Date de fin: 31 oct. 2011
PROJET
TERMINÉ
"A common trait to disorders such as type 2 diabetes or obesity is the development of insulin resistance. There is evidence indicating the existence of a bidirectional cross-talk between insulin signalling and mitochondrial function that may be relevant for the pathogenesis of those disorders. Based on this, MITIN main goal is to identify novel mitochondrial-dependent mechanisms responsible for the development of insulin resistance. This will be done by the use of technologies of Systems Biology and the generation of computer-based tools that will permit the study of complex biological systems that integrate different regulatory networks. For the global visualization and interpretation of the “insulin signalling/mitochondria” complex system we plan to develop a computational framework that will store and integrate all possible data for each of the subsystems, both currently available data and data generated within the project by transcriptomics and lipidomics analysis. This will allow the prediction of functional associations and interactions between both processes, which will be tested under specific hypothesis-driven studies in mammalian cells, mice and Drosophila. By using a Systems Biology approach and investigating how different perturbations modulate cell transcriptomes, and lipidomes, we aim to identify integrated homeostatic responses involving the insulin signalling network and the mitochondria networks. Validation of some of the strongest associations detected by virtue of the integrated systems biology of insulin signalling/mitochondria will generate high value targets of use in therapy against Complex Diseases such as diabetes, obesity, or pathophysiological traits of the Metabolic Syndrome. Besides, computer-based tools generated in the project will be applicable to the analysis of the mechanisms that trigger other Complex Diseases."
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