Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution.
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Authors
Dingle, Kamaludin
Publication Date
2022-03-15Journal Title
Proc Natl Acad Sci U S A
ISSN
0027-8424
Publisher
Proceedings of the National Academy of Sciences
Volume
119
Issue
11
Language
eng
Type
Article
This Version
VoR
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Johnston, I. G., Dingle, K., Greenbury, S. F., Camargo, C. Q., Doye, J. P., Ahnert, S., & Louis, A. A. (2022). Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution.. Proc Natl Acad Sci U S A, 119 (11) https://doi.org/10.1073/pnas.2113883119
Abstract
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.
Keywords
Development, Evolution, Algorithmic Information Theory
Identifiers
35275794, PMC8931234
External DOI: https://doi.org/10.1073/pnas.2113883119
This record's URL: https://www.repository.cam.ac.uk/handle/1810/336008
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/
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