Abstract
Today's subcellular and multicellular models of infection are poised to tackle bigger questions about virus-host interactions and the determinants of susceptibility. This opportunity comes from increased computing power, improved model architectures, and comprehensive datasets collected from virus-infected hosts. Here we summarize recent advances in viral modeling and data science that illustrate how systems models have successfully traversed increasing time-length scales, levels of detail, and ranges of biological context. The latest progress is encouraging, but recent findings just scratch the surface given how many different viruses exist or could someday emerge-the scale of the effort should align with the scale of the challenge. Abstraction of molecular and cellular networks by systems virology complements public-health models of viral transmission that are widely applied to human populations.