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Garret, Simon; Robbins, Martin; Walker, Joanne; Wilson, William; Aickelin, Uwe (2010)
Publisher: Springer
Languages: English
Types: Part of book or chapter of book
Subjects: Computer Science - Artificial Intelligence, Quantitative Biology - Cell Behavior, Computer Science - Neural and Evolutionary Computing
Accurate immunological models offer the possibility of performing highthroughput experiments in silico that can predict, or at least suggest, in vivo phenomena. In this chapter, we compare various models of immunological memory. We first validate an experimental immunological simulator, developed by the authors, by simulating several theories of immunological memory with known results. We then use the same system to evaluate the predicted effects of a theory of immunological memory. The resulting model has not been explored before in artificial immune systems research, and we compare the simulated in silico output with in vivo measurements. Although the theory appears valid, we suggest that there are a common set of reasons why immunological memory models are a useful support tool; not conclusive in themselves.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1 Computational Biology Group, Department of Computer Science, University of Wales, Aberystwyth, SY23 3PG. Wales, UK. {smg,mjr00}@aber.ac.uk
    • 2 School of Computer Science (ASAP), University of Nottingham, Nottingham, NG8 1BB. England, UK. {w.wilson,uwe.aickelin}@notts.ac.uk 5 0 + e 1 4
    • lcseeun 84e0+
    • ifrobemm e0640+
    • uN 44 0 + e 2 0 0 + e 0
    • m 0
    • im 0
    • m 0
    • im 0 0 0 0
    • s 1
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