This chapter describes the behavior of the immune system from an informationprocessing perspective. It reviews a series of projects conducted at the University of New Mexico and the Santa Fe Institute, which have developed and explored the theme "immunology as information processing." The projects cover the spectrum from serious modeling of real immunological phenomena, such as crossreactive responses in animals and the generation of diversity, to computer science applications, especially the attempt to develop an immune system for computers to protect them against viruses, intrusions, and other malicious activities. In each project, we have used an approach with the following steps: (1) Identify a specific mechanism that appears to be interesting computationally, (2) write a computer program that implements or models the mechanism, (3) study its properties through simulation and mathematical analysis, and (4) demonstrate its capabilities, either by applying the ...

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We have constructed a stochastic stage-structured model of the cytotoxic T lymphocyte (CTL) response to antigen and the maintenance of immunological memory. The model follows the the dynamics of a viral infection and the stimulation, proliferation, and differentiation of naive CD8+ T cells into effector CTL, which can eliminate virally infected cells. The model is capable of following the dynamics of multiple T cell clones, each with a T cell receptor represented by a digit string. MHC-viral peptide complexes are also represented by strings and a string match rule is used to compute the affinity of a T cell receptor for a viral epitope. The avidities of interactions are also computed by taking into consideration the density of MHC-viral peptides on the surface of an infected cell. Lastly, the model allows the probability of T cell stimulation to depend on avidity but also incorporates the notion of an antigen-independent programmed proliferative response. We compare the model to experimental data on the cytotoxic T cell response to lymphocytic choriomeningitis virus infections.

We have constructed a computer model of the cytotoxic T lymphocyte (CTL) response to antigen and the maintenance of immunological memory. Because immune responses often begin with small numbers of cells and there is great variation among individual immune systems, we have chosen to implement a stochastic model that captures the life cycle of T cells more faithfully than deterministic models. Past models of the immune response have been differential equation based, which do not capture stochastic effects, or agent-based, which are computationally expensive. We use a stochastic stage-structured approach that has many of the advantages of agent-based modeling but is much more efficient. Our model can provide insights into the effect infections have on the CTL repertoire and the response to subsequent infections.