Abstract
A comprehensive model of the immune classifier system is presented where the affinity between the epitope- paratope pairs is defined in terms of structural matching and compatibility with respect to important physicochemical and geometrical parameters. Effects of medium interactions (energy constraints) on adaptive maturation of affinity and clonal selection are also simulated in terms of certain cost functions. Results of implementation on some real data are presented focussing on the nonlinear effects of the probability and strength of binding interactions and the metadynamics of variation in system parameters. Importance and scope of the approach in understanding the complexity of the associated nonlinear stochastic (bio)system is highlighted.
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