Computational Modeling

Abstract

The immune system is highly complex and dynamic, encompassing hierarchical interactions with dimensions ranging from nanometers to meters and time scales from nanoseconds to years. Infectious and immune-mediated diseases involve changes spanning many spatiotemporal scales, but are generally studied in compartmentalized single-scale settings. Computational and mathematical modeling provides an avenue for integrating and standardizing diverse and complex data and knowledge to comprehensively understand unforeseen mechanisms across spatiotemporal scales. Models can be used to guide experimental designs of wet-lab experiments that will most efficiently narrow the range of mechanisms to be explored, to determine those time points at which data will best distinguish between alternative hypotheses concerning the time course of wet-lab experiments or clinical studies, to generalize from in vitro results to in vivo, from wild-type to knockout animals, and from one animal model to another. This chapter describes the modeling process and tools.