Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution

SignificanceWhy does evolution favor symmetric structures when they only represent a minute subset of all possible forms? Just as monkeys randomly typing into a computer language will preferentially produce outputs that can be generated by shorter algorithms, so the coding theorem from algorithmic i...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS Vol. 119; no. 11; p. e2113883119
Main Authors: Johnston, Iain G, Dingle, Kamaludin, Greenbury, Sam F, Camargo, Chico Q, Doye, Jonathan P K, Ahnert, Sebastian E, Louis, Ard A
Format: Journal Article
Language:English
Published: United States 15.03.2022
Subjects:
Algorithms
Biological Evolution
Gene Regulatory Networks
Information Theory
Phenotype
Selection, Genetic
algorithmic information theory
development
evolution
ISSN:1091-6490, 1091-6490
Online Access:Get more information
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Summary:SignificanceWhy does evolution favor symmetric structures when they only represent a minute subset of all possible forms? Just as monkeys randomly typing into a computer language will preferentially produce outputs that can be generated by shorter algorithms, so the coding theorem from algorithmic information theory predicts that random mutations, when decoded by the process of development, preferentially produce phenotypes with shorter algorithmic descriptions. Since symmetric structures need less information to encode, they are much more likely to appear as potential variation. Combined with an arrival-of-the-frequent mechanism, this algorithmic bias predicts a much higher prevalence of low-complexity (high-symmetry) phenotypes than follows from natural selection alone and also explains patterns observed in protein complexes, RNA secondary structures, and a gene regulatory network.
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ISSN:1091-6490
1091-6490
DOI:10.1073/pnas.2113883119