Computational modeling techniques and tools are playing increasingly important roles in advancing a system-level mechanistic understanding of biological processes. The in silico experimentation can help shape and guide experimental and clinical efforts. There are an array of tools that can be used to accelerate creation of mathematical models and therefore facilitate generation of in silico simulations. In this chapter, we will briefly review some of these tools and provide hands-on modeling examples. Finally, the chapter proposes an examination of the relationship between model complexity, reliability and knowledge discovery, and model-driven hypothesis generation.
|Original language||English (US)|
|Title of host publication||Computational Immunology|
|Subtitle of host publication||Models and Tools|
|Number of pages||26|
|State||Published - 2016|
All Science Journal Classification (ASJC) codes