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Immune Network

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Encyclopedia of Machine Learning and Data Mining
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A proposed theory that the immune system is capable of achieving immunological memory by the existence of a mutually reinforcing network of B-cells. This network of B-cells forms due to the ability of the paratopes, located on B-cells, to match against the idiotopes on other B-cells. The binding between the idiotopes and paratopes has the effect of stimulating the B-cells. This is because the paratopes on B-cells react to the idiotopes on similar B-cells, as it would an antigen. However, to counter the reaction there is a certain amount of suppression between the B-cells which acts as a regulatory mechanism. This interaction of the B-cells due to the network was said to contribute to a stable memory structure and account for the retainment of memory cells, even in the absence of antigen. This interaction of cells forms the basis of inspiration for a large number of AIS algorithms, for example aiNET.

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(2017). Immune Network. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_380

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