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The Swarming Body: Simulating the
Decentralized Defenses of Immunity
Christian Jacob
1
,
2
, Scott Steil
2
, and Karel Bergmann
2
1
Dept. of Biochemistry & Molecular Biology, Faculty of Medicine
2
Dept. of Computer Science, Faculty of Science
University of Calgary, Calgary, Alberta, Canada
Abstract.
We consider the human body as a well-orchestrated sys-
tem of interacting swarms. Utilizing swarm intelligence techniques, we
present our latest virtual simulation and experimentation environment,
IMMS:VIGO::3D
, to explore key aspects of the human immune system.
Immune system cells and related entities (viruses, bacteria, cytokines)
are represented as virtual agents inside 3-dimensional, decentralized and
compartmentalized environments that represent primary and secondary
lymphoid organs as well as vascular and lymphatic vessels. Specific im-
mune system responses emerge as by-products from collective interac-
tions among the involved simulated 'agents' and their environment. We
demonstrate simulation results for clonal selection and primary and sec-
ondary collective responses after viral infection, as well as the key
response patterns encountered during bacterial infection. We see this
simulation environment as an essential step towards a hierarchical whole-
body simulation of the immune system, both for educational and research
purposes.
1
Introduction
Computer-based tools and virtual simulations are changing the way of biological
research. Immunology is no exception. Computers become even more capable of
running large-scale models of complex biological systems. Recent advancements
in grid computing technologies make high-performance computer resources read-
ily accessible to almost everybody [1]. Consequently, even highly sophisticated
- and to a large extent still poorly understood - processes such as the inner
workings of immune system defense mechanisms can now be tackled by agent-
based models in combination with interactive visualization components. These
agent models serve as an essential complement to modeling approaches that are
traditionally more abstract and purely mathematical [6,7].
Our
Evolutionary & Swarm Design Laboratory
is building and promoting
agent-based models, with distributed simulation and visualization capabilities,
utilizing swarm intelligence methodologies [2]. The combination of visual and
intuitive user interfaces, in combination with the latest technology in visualiza-
tion (including 3D-immersive environments in CAVES) and distributed high-
performance computing, makes our models more accessible to researchers in the
