The complex differentiation process of the CD4+ T helper lymphocytes shapes the form and the range of the immune response to different antigenic challenges. Few mathematical and computational models have addressed this key phenomenon. We here present a multiscale approach in which two different levels of description, i.e. a gene regulatory network model and an agent-based simulator for cell population dynamics, are integrated into a single immune system model.

It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements.