Relevance of pattern recognition in a non-deterministic model of immune responses

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Abstract

An artificial immune system model which lacks an explicit pattern recognition mechanism, yet appears to explain immunological memory and immune responses had been proposed[1, 2]. In this study, I asked whether inclusion of a pattern recognition mechanism (antigen-antibody) in the same computer simulation would substantially change the outcomes and thus the explanatory power of the proposed model. Our results suggest that although antigen-antibody interactions can elicit the emergence of an immune response, their relevance is contingent on the previous condition of the system, that is, the starting balance between suppressive and reactive agents (attractor) and its distance from the threshold for an inflammatory response. I conclude that changing the attractor (which maintain the level of reactivity in the background) is more important for the emergence or non-emergence of immune responses than modifying the pattern recognition system. © 2011 Springer-Verlag.

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Salazar-Bañuelos, A. (2011). Relevance of pattern recognition in a non-deterministic model of immune responses. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6825 LNCS, pp. 108–116). https://doi.org/10.1007/978-3-642-22371-6_12

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