Agent-Based Modeling and High Performance Computing

Maksudul Alam, Vida Abedi, Josep Bassaganya-Riera, Katherine Wendelsdorf, Keith Bisset, Xinwei Deng, Stephen Eubank, Raquel Hontecillas, Stefan Hoops, Madhav Marathe

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationComputational Immunology
Subtitle of host publicationModels and Tools
PublisherElsevier Inc.
Number of pages33
ISBN (Electronic)9780128037157
ISBN (Print)9780128036976
StatePublished - 2016

All Science Journal Classification (ASJC) codes

  • General Medicine


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