PlumX Metrics
Embed PlumX Metrics

Gene networks have a predictive long-term fitness

GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference, Page: 727-734
2013
  • 0
    Citations
  • 0
    Usage
  • 15
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Conference Paper Description

Using a model of evolved gene regulatory networks, we illustrate several quantitative metrics relating to the long-term evolution of lineages. The k-generation fitness and k-generation survivability measure the evolutionary success of lineages. An entropy measure is used to quantify the predictability of lineage evolution. The metrics are readily applied to any system in which lineage membership can be periodically counted, and provide a quantitative characterization of the genetic landscape, genotype-phenotype map, and fitness landscape. Evolution is shown to be surprisingly predictable in gene networks: only a small number of the possible outcomes are ever observed in multiple replicate experiments. We emphasize the view that the lineage (not the individual, or the genotype) is the evolving entity over the long term. Notably, the long-term fitness is distinct from the short-term fitness. Since evolution is repeatable over the long-term, this implies long-term selection on lineages is possible; the evolutionary process need not be "short-sighted". If we wish to evolve very complex artifacts, it will be expedient to promote the long-term evolution of the genetic architecture by tailoring our models to emphasize long-term selection. Copyright © 2013 ACM.

Bibliographic Details

Michael E. Palmer

Association for Computing Machinery (ACM)

Biochemistry, Genetics and Molecular Biology; Mathematics

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know