By Jose Faro, Jaime Combadao, Isabel Gordo (auth.), Hugues Bersini, Jorge Carneiro (eds.)
ICARIS 2006 is the ?fth example of a chain of meetings devoted to the comprehension and the exploitation of immunological ideas via their translation into computational phrases. All scienti?c disciplines wearing a reputation that starts with “arti?cial” (followed through “life,” “reality,” “intelligence” or “- munesystem”) aresimilarlysu?ering froma veryambiguousidentity.Their axis of study attempts to stabilize an on-going identification someplace within the crossroad of engineering (building priceless artifacts), average sciences (biologyor psychology— enhancing the comprehension and prediction of ordinary phenomena) and t- oretical laptop sciences (developing and gaining knowledge of the algorithmic world). for this reason and reckoning on which of those views gets extra s- port, they try at attracting di?erent different types of scientists and at stimul- ing di?erent types of scienti?c attitudes. for a few years and within the past ICARIS meetings, it was once sincerely the “engineering” viewpoint that was once the main represented and prevailed in the course of the guides. certainly, because the o- gin of engineering and expertise, nature has o?ered a reserve of inexhaustible inspirations that have prompted the improvement of worthy artifacts for guy. Biology has resulted in the advance of recent computing device instruments, similar to genetic - gorithms, Boolean and neural networks, robots studying by means of adventure, mobile machines and others that create a brand new imaginative and prescient of IT for the engineer: parallel, ?exible andautonomous.Inthis kind of informatics,complexproblemsareta- led through uncomplicated mechanisms, yet in?nitely iterated in time and space.
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Additional resources for Artificial Immune Systems: 5th International Conference, ICARIS 2006, Oeiras, Portugal, September 4-6, 2006. Proceedings
Regulatory T cells selectively express toll-like receptors and are activated by lipopolysaccharide. J. Exp. Med. 197(4) (2003) 403–411 16. : Immunological self-tolerance: Lessons from mathematical modeling. Journal of Computational and Applied Mathematics 184(1) (2005) 77–100 17. : Modelling viral and immune system dynamics. Nature Reviews in Immunology 2 (2002) 28–36 18. : A computer model of cellular interactions in the immune system. Immunology Today 13(2) (1992) 56–62 19. : Elementary Diﬀerential Equations and Boundary Value Problems.
Inﬂuenza virus receptors in the human airway. Nature 440(7083) (2006) 435–436 29. : H5N1 virus attachment to lower respiratory tract. Science 312(5772) (2006) 399 Originally published in Science Express on 23 March 2006. ¨ 30. : Transcode. org. (2001) 31. : MASyV: A Multi-Agent System Visualization package. net. (2003) 32. : Probing the eﬀects of the well-mixed assumption on viral infection dynamics. J. Theor. Biol. CB/0505043. Cellular Frustration: A New Conceptual Framework for Understanding Cell-Mediated Immune Responses F.
T cells can also contact many different types of target cells in the effector phase. Cytotoxic T cells for example monitor all the cells of the body. Interestingly, even neuronal cells have been described to influence T cell function . Interactions among T cells themselves play an important role in regulatory activities of the immune system. Regulatory T cells can either target effector T cells directly  or modulate the T cell activating capacity of APC [17, 27]. Anergic T cells in their turn can pass on immune responsiveness by down regulation of other T cell responses [28, 29].