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Using Lazy Evaluation to Simulate Realistic-Size Repertoires in Models of the Immune System

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Abstract

We describe a method of implementing efficient computer simulations of immune systems that have a large number of unique B and/or T cell clones. The method uses an implementation technique called lazy evaluation to create the illusion that all clones are being simulated, while only actually simulating a much smaller number of clones that can respond to the antigens in the simulation. The method is effective because only 0.001% to 0.01% of clones can typically be simulated by an antigen, and because many simulations involve only a small number of distinct antigens. A lazy simulation of a realistic number of clones and 10 distinct antigens is 1,000 times faster and 10,000 times smaller than a conventional simulation---making simulations of immune systems with realistic-size repertoires computationally tractable.

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  • Derek J. Smith & Stephanie Forrest & David H. Ackley & Alan S. Perelson, 1997. "Using Lazy Evaluation to Simulate Realistic-Size Repertoires in Models of the Immune System," Working Papers 97-09-078, Santa Fe Institute.
    • Handle: RePEc:wop:safiwp:97-09-078
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    1. Derek J. Smith & Stephanie Forrest & Ron R. Hightower & Alan S. Perelson, 1997. "Deriving Shape Space Parameters from Immunological Data for a Model of Cross-Reactive Memory," Working Papers 97-03-017, Santa Fe Institute.
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