Traditionally, in vivo and in vitro experimentation has been the only way to study viral infections. This approach for deriving knowledge based solely on experimental observations relies on common-sense assumptions (e.g., a higher virus count means a fitter virus). These assumptions often go untested due to difficulties controlling individual components of these complex systems without affecting others. The use of mathematical models and computer simulations to describe such systems, however, makes it possible to deconstruct an experimental system into individual components and determine how the pieces combine to create the infection we observe.