Genetic algorithms and the immune system

Stephanie Forrest, Alan S. Perelson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

38 Scopus citations

Abstract

Using genetic algorithm techniques we introduce a model to examine the hypothesis that antibody and T cell receptor genes evolved so as to encode the information needed to recognize schemas that characterize common pathogens. We have implemented the algorithm on the Connection Machine for 16,384 64-bit antigens and 512 64-bit antibodies.

Original languageEnglish (US)
Title of host publicationParallel Problem Solving from Nature - 1st Workshop, PPSN I, Proceedings
EditorsHans-Paul Schwefel, Reinhard Manner
PublisherSpringer Verlag
Pages320-325
Number of pages6
ISBN (Print)9783540541486
DOIs
StatePublished - Jan 1 1991
Externally publishedYes
Event1st Workshop on Parallel Problem Solving from Nature, PPSN 1990 - Dortmund, Germany
Duration: Oct 1 1990Oct 3 1990

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume496 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st Workshop on Parallel Problem Solving from Nature, PPSN 1990
CountryGermany
CityDortmund
Period10/1/9010/3/90

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Forrest, S., & Perelson, A. S. (1991). Genetic algorithms and the immune system. In H-P. Schwefel, & R. Manner (Eds.), Parallel Problem Solving from Nature - 1st Workshop, PPSN I, Proceedings (pp. 320-325). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 496 LNCS). Springer Verlag. https://doi.org/10.1007/BFb0029771