The combination of experimental and computational methods provides a powerful approach for understanding biological processes. Initial experiments can suggest hypotheses that can be captured by first-generation mathematical/ computational models (henceforth simply called 'mathematical models' or 'models'), which can then be employed to generate new experimental approaches to test those models. Understanding signal transduction pathways, with their myriad of molecular interactions, feedback loops, and spatial and temporal variations in concentrations of key molecules, requires such an iterative process between experiments and modeling.