The chapters in this volume have thus far primarily described the properties of individual endothelial cells (ECs) as well as the behavior of the endothelium as a whole organ. But how is that transition from individual cellular function to organ-level behavior made? Merely extrapolating the behavior of individual ECs is insufficient; the internal heterogeneity of the endothelial organ precludes linear summation of individual EC function. Rather, it is necessary to place the behavior of the ECs in the context of their local environment, be that in various tissue beds in a baseline state of health or in pathological regional disruptions associated with injury or infection. What is required is a means of formalizing the process by which the laboratory-derived data about individual ECs can be translated into the richness of behavior that is seen at the level of an organism. Systems biology and mathematical modeling can provide a mechanism for this translation, and this chapter will introduce one of these techniques, agent based modeling (ABM), and give an example of an ABM that includes endothelial function.

WHAT IS AGENT-BASED MODELING?

ABM is a type of mathematical modeling that is dynamic (evolving over time), discrete-event (stepwise progression of time and action), and mechanistic (dependent upon rules). ABM is completely deterministic, meaning that, for a specific set of initial conditions, the model will run exactly the same for each simulation run. However, stochasticity built into the model at multiple levels (through the use of random-number generators) allows for variation in the models' dynamics. The emphasis with ABM is on the individual components of a dynamic system and the rules that govern them.