Agent-Based Modeling and High Performance Computing

Agent-based modeling is a computational modeling framework for simulating the interactions of multiple diverse agents representing a complex system or phenomenon. The appoach has been successfully used to model a number of social, biological, and technological systems. In this chapter, we present ENteric Immunity SImulator (ENISI), an agent-based modeling framework for studying the inflammatory and regulatory immune pathways triggered by interactions among microbes and immune cells in the gut. In ENISI, individual cells move through simulated tissues and engage in context-dependent interactions with the other cells with which they are in contact. The scale of ENISI is unprecedented in this domain, with the ability to simulate 10⁷-10⁹ cells for 250 simulated days in 90min on a modest cluster. We describe the formal representation of the immune system as an agent-based model for modeling mucosal immune responses to gastrointestinal pathogens. We also describe performance and sensitivity analysis techniques and demonstrate the utility of ENISI in guiding the design of wet-lab experiments.