Research in virophysics typically focuses on resolving the physical structure and structural properties of viruses, the dynamics of their assembly and disassembly, their population kinetics over the course of an infection, and the emergence and evolution of various strains. The common aim of these efforts is to establish a set of models (expressions or laws) that quantitatively describe the details of all processes involved in viral infections with reliable predictive power. Having such a quantitative understanding of viruses would not only rationalize the development of strategies to prevent, guide, or control the course of viral infections, but could also be used to exploit virus processes and put virus to work in areas such as nanosciences, materials, and biotechnologies. 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. == Overlap with other fields ==