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Swarm-Based Simulations for Immunobiology

What Can Agent-Based Models Teach Us about the Immune System?

  • Chapter
Information Processing and Biological Systems

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 11))

Abstract

In this contribution, we present a computer model of information processing within a highly distributed biological system of the human body, which is orchestrated over multiple scales of time and space: the immune system. We consider the human body and its environment as a well-orchestrated system of interacting swarms: swarms of cells, swarms of messenger molecules, swarms of bacteria, and swarms of viruses. Utilizing swarm intelligence techniques, we present three virtual simulations and experiments 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 compartments that represent primary and secondary lymphoid organs as well as vascular and lymphatic vessels. Specific immune system responses emerge as by-products from collective interactions among the involved simulated ‘agents’ and their environment. We demonstrate simulation results for clonal selection in combination with primary and secondary collective responses after viral infection. We also model, simulate, and visualize key response patterns encountered during bacterial infection. As a third model we consider the complement system, for which we present initial simulation results. We consider these in-silico experiments and their associated modeling environments as an essential step towards hierarchical whole-body simulations of the immune system, both for educational and research purposes.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, University of Calgary, Canada

    Christian Jacob, Vladimir Sarpe & Carey Gingras

  2. Dept. of Biochemistry and Molecular Biology, University of Calgary, Canada

    Christian Jacob

  3. Center for Immunobiology and Vaccine Development, Children’s Hospital Oakland Research Institute, Oakland, CA, USA

    Rolando Pajon Feyt

Authors
  1. Christian Jacob
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  2. Vladimir Sarpe
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  3. Carey Gingras
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  4. Rolando Pajon Feyt
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Editor information

Editors and Affiliations

  1. Department of Signal Processing , Tampere University of Technology, POB 553, 33101, Tampere, Finland

    Samuli Niiranen  & Andre Ribeiro  & 

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Jacob, C., Sarpe, V., Gingras, C., Feyt, R.P. (2011). Swarm-Based Simulations for Immunobiology. In: Niiranen, S., Ribeiro, A. (eds) Information Processing and Biological Systems. Intelligent Systems Reference Library, vol 11. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19621-8_3

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  • DOI: https://doi.org/10.1007/978-3-642-19621-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19620-1

  • Online ISBN: 978-3-642-19621-8

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