System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Computing in Science and Engineering
A new kind of science
Stochastic Stage-structured Modeling of the Adaptive Immune System
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Simulating antigenic drift and shift in influenza A
Proceedings of the 2009 ACM symposium on Applied Computing
Adaptive immunity-based multiagent systems (AIBMAS) inspired by the idiotypic network
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
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Immunological simulations offer the possibility of performing high-throughput experiments in silico that can predict, or at least suggest, in vivo phenomena. In this paper, 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. We conclude that the theory appears valid, but that there are a common set of reasons why simulations are a useful support tool, not conclusive in themselves.