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.