In the era of post-genomic research two new disciplines, Systems and Synthetic biology, act in a complementary way to shed light on the ever-increasing amount of data produced by novel high-throughput techniques. Systems biology aims at developing a formal understanding of biological processes through the development of quantitative mathematical models (bottom-up approach) and of 'reverse engineering' (top-down approach), whose aim is to infer the interactions among genes and proteins from experimental observations (gene regulatory networks). Synthetic biology on the other hand uses mathematical models to design novel biological 'circuits' (synthetic networks) able to perform specific tasks (for example, periodic expression of a gene of interest), or able to change the behavior of a biological process in a desired way (for example, modify metabolism to produce a specific compound of interest). The use of a pioneering approach that combines biology and engineering, to describe and/or invent new behaviors, could represent a valuable resource for studying complex diseases and design novel therapies. The identification of regulatory networks will help in identifying hundreds of genes that are responsible for most genetic diseases and that could serve as a starting point for therapeutic intervention. Here we present some of the main genetics and medical applications of these two emerging fields.