The coevolution of mutation rates

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

1 Scopus citations

Abstract

In order to better understand life, it is helpful to look beyond the envelop of llfe as we know it. A simple model of coevolution was implemented with the addition of genes for longevity and mutation rate in the individuals. This made it possible for a lineage to evolve to be immortal. It also allowed the evolution of no mutation or extremely high mutation rates. The model shows that when the individuals interact in a sort of zero-sum game, the lineages mmntain relatively high mutation rates. However, when individuals engage in interactions that have greater consequences for one individual in the interaction than the other, lineages tend to evolve relatively low mutation rates. This model suggests that different genes may have evolved different mutation rates as adaptations to the varying pressures of interactions with other genes.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages219-233
Number of pages15
Volume929
ISBN (Print)3540594965, 9783540594963
DOIs
StatePublished - 1995
Externally publishedYes
Event3rd European Conference on Artificial Life, ECAL 1995 - Granada, Spain
Duration: Jun 4 1995Jun 6 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume929
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd European Conference on Artificial Life, ECAL 1995
CountrySpain
CityGranada
Period6/4/956/6/95

    Fingerprint

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Maley, C. (1995). The coevolution of mutation rates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 929, pp. 219-233). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 929). Springer Verlag. https://doi.org/10.1007/3-540-59496-5_301