Using an agent-based model to analyze the dynamic communication network of the immune response |
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| Authors: | Virginia A Folcik Gordon Broderick Shunmugam Mohan Brian Block Chirantan Ekbote John Doolittle Marc Khoury Luke Davis and Clay B Marsh |
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| Institution: | (1) Department of Internal Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Davis Heart and Lung Research Institute, The Ohio State University Medical Center, Columbus, OH, USA;(2) Department of Medicine, University of Alberta, Edmonton, Alberta, Canada;(3) Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA;(4) Department of Medicine Administration, The Ohio State University Medical Center, Columbus, OH, USA |
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| Abstract: | Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines.
While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge.
The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines,
chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically
in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from
the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the
interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing
knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics,
ultimately for the design of therapeutic interventions. |
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