• Endless forms most beautiful: Why evolut

    From ScienceDaily@1:317/3 to All on Mon Mar 14 22:30:38 2022
    Endless forms most beautiful: Why evolution favors symmetry

    Date:
    March 14, 2022
    Source:
    The University of Bergen
    Summary:
    An international team of researchers from biology, computer
    science and mathematics explains why evolution has a preference
    for symmetry.



    FULL STORY ==========================================================================
    From sunflowers to starfish, symmetry appears everywhere in biology. This
    isn't just true for body plans -- the molecular machines keeping our
    cells alive are also strikingly symmetric. But why? Does evolution have
    a built-in preference for symmetry?

    ==========================================================================
    An international team of researchers believe so, and have combined ideas
    from biology, computer science and mathematics to explain why. As they
    report inPNAS, symmetric and other simple structures emerge so commonly
    because evolution has an overwhelming preference for simple "algorithms"
    -- that is, simple instruction sets or recipes for producing a given
    structure.

    "Imagine having to tell a friend how to tile a floor using as few words as possible," says Iain Johnston, a professor at the University of Bergen and author on the study. "You wouldn't say: put diamonds here, long rectangles here, wide rectangles here. You'd say something like: put square tiles everywhere. And that simple, easy recipe gives a highly symmetric
    outcome." The team used computational modeling to explore how this
    preference comes about in biology. They showed that many more possible
    genomes describe simple algorithms than more complex ones. As evolution searches over possible genomes, simple algorithms are more likely to be discovered -- as are, in turn, the more symmetric structures that they
    produce. The scientists then connected this evolutionary picture to a deep result from the theoretical discipline of algorithmic information theory.

    "These intuitions can be formalized in the field of algorithmic
    information theory, which provides quantitative predictions for the
    bias towards descriptive simplicity," says Ard Louis, professor at the University of Oxford and corresponding author on the study.

    The study's key theoretical idea can be illustrated by a twist on a famous thought experiment in evolutionary biology, which pictures a room full of monkeys trying to write a book by typing randomly on a keyboard. Imagine
    the monkeys are instead trying to write a recipe. Each is far more likely
    to randomly hit the letters required to spell out a short, simple recipe
    than a long, complicated one. If we then follow any recipes the monkeys
    have produced -- our metaphor for producing biological structures from
    genetic information - - we will produce simple outcomes much more often
    than complicated ones.

    The scientists show that a wide range of biological structures
    and systems, from proteins to RNA and signaling networks, adopt
    algorithmically simple structures with probabilities as predicted by
    this theory. Going forward, they plan to investigate the predictions that
    their theory makes for biases in larger-scale developmental processes.


    ========================================================================== Story Source: Materials provided by The_University_of_Bergen. Note:
    Content may be edited for style and length.


    ========================================================================== Related Multimedia:
    * Strikingly_symmetric_molecular_machinery ========================================================================== Journal Reference:
    1. Iain G. Johnston, Kamaludin Dingle, Sam F. Greenbury, Chico
    Q. Camargo,
    Jonathan P. K. Doye, Sebastian E. Ahnert, Ard A. Louis. Symmetry
    and simplicity spontaneously emerge from the algorithmic nature
    of evolution.

    Proceedings of the National Academy of Sciences, 2022; 119 (11)
    DOI: 10.1073/pnas.2113883119 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/03/220314095742.htm

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