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Reconstructing networks from experimental and natural genetic perturbations
This video was recorded at Learning and Inference in Computational Systems Biology (LICSB), Warwick 2010. Functional genomics has demonstrated considerable success in inferring the inner working of a cell through analysis of its response to various perturbations. Perturbations can take the form of experimental interventions, like gene deletions or RNA interference, or natural perturbations, like SNPs or copy-number alterations. In my talk I will describe methods my lab has developed to reconstruct networks from the phenotypic effects of gene perturbations. In particular, I will (1) describe Nested Effects Models, a class of probabilistic graphical to reconstruct signaling pathways from downstream effects, and (2) introduce methods to correlate the impact of copy-number variation on gene expression with different sub-types of breast cancer.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
