• Integer mathematics and evolution

    From RonO@21:1/5 to All on Sun Aug 6 11:41:29 2023
    https://www.sciencedaily.com/releases/2023/08/230801131650.htm

    Science daily has an article about some math that doesn't seem to be so surprising. Why wouldn't integer mathematics apply to the possible
    evolution of RNA secondary structure and protein folding when there are
    no partial amino acids or nucleotides? You have a set integer number of nucleotides for any RNA secondary structure. Even deletions and
    insertions have to change by a specific integer number of units.

    https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0169

    Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve
    Vaibhav Mohanty, Sam F. Greenbury, Tasmin Sarkany, Shyam Narayanan,
    Kamaludin Dingle, Sebastian E. Ahnert and Ard A. Louis
    Published:26 July 2023https://doi.org/10.1098/rsif.2023.0169
    Abstract
    Phenotype robustness, defined as the average mutational robustness of
    all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an
    evolving population. By applying results from coding theory, we prove
    that the maximum phenotype robustness occurs when genotypes are
    organized as bricklayer’s graphs, so-called because they resemble the
    way in which a bricklayer would fill in a Hamming graph. The value of
    the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype–phenotype maps for RNA secondary structure and
    the hydrophobic-polar (HP) model for protein folding can exhibit
    phenotype robustness that exactly attains this upper bound. By
    exploiting properties of the sums-of-digits function, we prove a lower
    bound on the deviation of the maximum robustness of phenotypes with
    multiple neutral components from the bricklayer’s graph bound, and show
    that RNA secondary structure phenotypes obey this bound. Finally, we
    show how robustness changes when phenotypes are coarse-grained and
    derive a formula and associated bounds for the transition probabilities
    between such phenotypes.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Glenn@21:1/5 to RonO on Sun Aug 6 14:13:26 2023
    On Sunday, August 6, 2023 at 9:46:04 AM UTC-7, RonO wrote:
    https://www.sciencedaily.com/releases/2023/08/230801131650.htm

    Science daily has an article about some math that doesn't seem to be so surprising. Why wouldn't integer mathematics apply to the possible
    evolution of RNA secondary structure and protein folding when there are
    no partial amino acids or nucleotides? You have a set integer number of nucleotides for any RNA secondary structure. Even deletions and
    insertions have to change by a specific integer number of units.

    https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0169

    Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve
    Vaibhav Mohanty, Sam F. Greenbury, Tasmin Sarkany, Shyam Narayanan, Kamaludin Dingle, Sebastian E. Ahnert and Ard A. Louis
    Published:26 July 2023https://doi.org/10.1098/rsif.2023.0169
    Abstract
    Phenotype robustness, defined as the average mutational robustness of
    all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove
    that the maximum phenotype robustness occurs when

    Seems odd that coding theory knows anything about phenotype robustness, but I suppose it can since they proved it.

    genotypes are
    organized as bricklayer’s graphs, so-called because they resemble the
    way in which a bricklayer would fill in a Hamming graph. The value of
    the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype–phenotype maps for RNA secondary structure and
    the hydrophobic-polar (HP) model for protein folding can exhibit
    phenotype robustness that exactly attains this upper bound. By
    exploiting properties of the sums-of-digits function, we prove a lower
    bound on the deviation of the maximum robustness of phenotypes with
    multiple neutral components from the bricklayer’s graph bound, and show that RNA secondary structure phenotypes obey this bound. Finally, we
    show how robustness changes when phenotypes are coarse-grained and
    derive a formula and associated bounds for the transition probabilities between such phenotypes.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From RonO@21:1/5 to Glenn on Mon Aug 7 05:34:51 2023
    On 8/6/2023 4:13 PM, Glenn wrote:
    On Sunday, August 6, 2023 at 9:46:04 AM UTC-7, RonO wrote:
    https://www.sciencedaily.com/releases/2023/08/230801131650.htm

    Science daily has an article about some math that doesn't seem to be so
    surprising. Why wouldn't integer mathematics apply to the possible
    evolution of RNA secondary structure and protein folding when there are
    no partial amino acids or nucleotides? You have a set integer number of
    nucleotides for any RNA secondary structure. Even deletions and
    insertions have to change by a specific integer number of units.

    https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0169

    Maximum mutational robustness in genotype–phenotype maps follows a
    self-similar blancmange-like curve
    Vaibhav Mohanty, Sam F. Greenbury, Tasmin Sarkany, Shyam Narayanan,
    Kamaludin Dingle, Sebastian E. Ahnert and Ard A. Louis
    Published:26 July 2023https://doi.org/10.1098/rsif.2023.0169
    Abstract
    Phenotype robustness, defined as the average mutational robustness of
    all the genotypes that map to a given phenotype, plays a key role in
    facilitating neutral exploration of novel phenotypic variation by an
    evolving population. By applying results from coding theory, we prove
    that the maximum phenotype robustness occurs when

    Seems odd that coding theory knows anything about phenotype robustness, but I suppose it can since they proved it.

    They didn't prove anything. All they did was determine that a type of sum-of-digits function would produce the pattern we observe of the
    accumulation of neutral mutations in the genomes of organisms as they
    evolved. These are the neutral changes that Yockey was talking about
    when he claimed that the pattern of substitutions in the protein that he
    was looking at was much less likely to have occurred by chance all at
    the same time than the probability of constructing his 100 amino acid
    long protein in any specific sequence. The changes have to not be
    selected against, and they have to occur in a pattern that reflects
    descent with modification in order to produce the phylogenies that occur
    in nature.

    The cytochrome c protein didn't just have one sequence, but the various lineages had their own sequence. Denton pointed out that each
    multicellular animal lineage had about the same number of substitutions
    from some ancestral protein sequence (all lineages have been evolving
    for the same length of time from a common ancestor), but he left out the
    fact that substitutions created a pattern. Some species were closely
    related like chimps and humans that had an identical sequence. Both
    chimps and humans had the same number of amino acid substitutions from
    the ancestral protein sequence, because they had an identical sequence
    and there hadn't been enough time for substitutions to occur in the
    lineages after they had separated, but both chimps and humans were 2 substitutions different from monkeys, and a few more different from
    rats. The protein sequences showed a pattern of genetic relationships
    that could be generated by descent with modification, but as Yockey
    pointed out, were highly unlikely to have occurred in their current
    pattern reflecting biological evolution than by chance.

    Ron Okimoto

    genotypes are
    organized as bricklayer’s graphs, so-called because they resemble the
    way in which a bricklayer would fill in a Hamming graph. The value of
    the maximal robustness is given by a fractal continuous everywhere but
    differentiable nowhere sums-of-digits function from number theory.
    Interestingly, genotype–phenotype maps for RNA secondary structure and
    the hydrophobic-polar (HP) model for protein folding can exhibit
    phenotype robustness that exactly attains this upper bound. By
    exploiting properties of the sums-of-digits function, we prove a lower
    bound on the deviation of the maximum robustness of phenotypes with
    multiple neutral components from the bricklayer’s graph bound, and show
    that RNA secondary structure phenotypes obey this bound. Finally, we
    show how robustness changes when phenotypes are coarse-grained and
    derive a formula and associated bounds for the transition probabilities
    between such phenotypes.


    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)