A Beginner’s Guide to Systems Simulation in Immunology

  • Grazziela P. Figueredo
  • Peer-Olaf Siebers
  • Uwe Aickelin
  • Stephanie Foan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7597)


Some common systems modelling and simulation approaches for immune problems are Monte Carlo simulations, system dynamics, discrete-event simulation and agent-based simulation. These methods, however, are still not widely adopted in immunology research. In addition, to our knowledge, there is few research on the processes for the development of simulation models for the immune system. Hence, for this work, we have two contributions to knowledge. The first one is to show the importance of systems simulation to help immunological research and to draw the attention of simulation developers to this research field. The second contribution is the introduction of a quick guide containing the main steps for modelling and simulation in immunology, together with challenges that occur during the model development. Further, this paper introduces an example of a simulation problem, where we test our guidelines.


Cellular Automaton Memory Cell System Simulation Simulation Approach System Dynamic Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Grazziela P. Figueredo
    • 1
  • Peer-Olaf Siebers
    • 1
  • Uwe Aickelin
    • 1
  • Stephanie Foan
    • 1
  1. 1.Intelligent Modelling and Analysis Research Group, School of Computer ScienceThe University of NottinghamUK

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