The development of personalized medicine requires being able to predict which mutations will or will not affect a phenotype of interest and to understand how these effects take place. We can address this challenge by studying model organisms and measuring what the effects of a large number of mutations are and learning from them what are the mechanisms by which mutations affect the function of the cell. We are developing tools that allow dissecting cellular networks by systematically perturbing them at the genetic level in order to understand the molecular bases of their robustness and sensitivity to mutations. Our approach combines the use of large-scale genetics to introduce mutations into protein interaction networks and the use of systems biology to measure how these mutations affect the network at the structural level. Our approach will allow to better understand how and why some mutations are tolerated by the cell while others are not and lead to diseases such as cancer.