Although many factors (molecules or complexes) are known to have a role during the progress of respiratory infection caused by influenza viruses, yet it is unknown where, when, and in what context this role takes place. Revealing the context of activity is key to understanding mechanisms of in vivo infection and how to modulate and prevent susceptibility to infections. In the IGV-FLU project, we proposed to address this challenge through identification of key drivers together with their timing and location of activity. In particular, we exploited the natural genetic variation to collect biological factors, constructed a comprehensive dynamic network model of in vivo infection, and used this model to uncover and validate potential drivers of susceptibility to influenza virus infection.