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

Derek J. Smith, Stephanie Forrest, David H. Ackley and Alan S. Perelson
Additional contact information
Stephanie Forrest: http://www.cs.unm.edu/~forrest/
David H. Ackley: http://www.cs.unm.edu/~ackley/

Working Papers from Santa Fe Institute

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.

Keywords: lazy evaluation; simulation; immune system; cross-reactive memory (search for similar items in EconPapers)
Date: 1997-09
References: View references in EconPapers View complete reference list from CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wop:safiwp:97-09-078

Access Statistics for this paper

More papers in Working Papers from Santa Fe Institute Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().