The Systems Biology home area focuses on the interface between computational/mathematical/statistical (“dry lab”) toolsets and experimental (“wet lab”) approaches that leverage their power. In regards to the “dry lab”, training emphasizes the complementarity of “Big Data”, i.e. data-driven machine learning approaches, and “Big Knowledge”, the construction of mechanistic models based on accumulated knowledge from the literature. In regards to the “wet lab”, Systems Biology training aims to equip students with expertise in experimental approaches so they may innovate and integrate them with computational/statistical analysis approaches.