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Modelling in systems genetics: computational approaches for discovering disease networks

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If you have a question about this talk, please contact Florian Markowetz .

One of the central hypotheses of systems biology is that molecular networks regulate protein levels which affect physiological states. When perturbed by genetic or environmental factors, these networks may become dysfunctional, and the corresponding physiological function is compromised. In human populations, naturally occuring DNA variants together with environmental perturbations induce changes in mRNA expression levels from which molecular disease networks can be reconstructed. We will present reverse-engineering algorithms to predict disease networks from integrated genetics, genomics and clinical data and demonstrate their application to reveal the tissue distribution of inherited risk for coronary artery disease (CAD), using a dataset of more than 700 microarrays profiled in up to 9 different vascular and metabolic tissues for 150 patients who were genotyped using SNP arrays (the STAGE cohort).

This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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