title: BioLogic: A mathematical modeling framework for immunologists.
abstract: The immune response to pathogens is a result of complex interactions among many cell types and a large number of molecular processes. As such it poses numerous challenges for modeling, simulation, and analysis. In this work we aim at addressing major issues regarding modeling of large biological systems with a special focus on the immune system. We address (1) the hierarchy in the system, from genes to organelles to cells to organs to organism, (2) the high variability due to experimentation, (3) the high variability among organisms, and (4) the need to bridge between immunologists/experimentalists and mathematicians/modelers. We provide an intuitive syntax to describe biological knowledge in terms of interactions (reactions) and objects (cells, organs, etc.) and illustrate how to use it in describing very complex systems. We describe the main elements of a simulation program that use that syntax to define models and to automatically simulate them. We restrict our discussion to modeling using logical network, although other modeling techniques, for example, differential equations and probabilistic/stochastic modeling, are also possible. Examples demonstrating the different features of the framework are given throughout the chapter.
authors.affiliation: Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
authors.forename: Shlomo
authors.initials: S
authors.lastname: Ta'asan
authors.forename: Rima
authors.initials: R
authors.lastname: Gandlin
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D007107:Immune System / Q000502:physiology*; D018448:Models, Immunological; D008962:Models, Theoretical