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Protein families are still improbably astonishing – retraction of Matlock and Swamidass paper in order?

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That is, if you write a realistic evolutionary simulation, instead of a simplistic one. From Kirk Durston at Contemplations:

A Response to Matlock and Swamidass on the Astonishing Improbability of Protein Families

In their simulation, they began with a perfectly ordered repeating sequence and then mutate it to see if the estimated functional information for non-functional sequences would converge on the actual value of zero bits of information. It did not, producing estimates that were significantly in error from the known value of zero bits. They provided no analysis as to why their results were so badly off.

I wrote a more realistic simulation that began with the same, highly ordered repeating sequence. From that seed sequence the program produces a universal common ancestral population from which numerous, independently evolving populations can be produced. The user can vary the length of the sequences, size of the populations, number of populations that descend from the universal ancestral population, percentage of sequences in each generation that produce progeny, mutation rate, and number of generations through which the populations evolve. Members of each generation that produced progeny are randomly chosen.

Try it for yourself: The program and modules are available here. One can try a range of values to see their effect. Caution: it is best to start small, as certain combinations of large values can easily result in run times of many hours, days, or even weeks.

A more realistic simulation falsifies the conclusions in the Matlock and Swamidass paper. At present, their paper falls substantially short of the standard we should expect for science, and requires significant revision if it is to be salvaged. More likely, it should be retracted from the public archive bioRxiv. Furthermore, a more realistic simulation not only falsifies their conclusions, but provides reason to believe that the method I presented in my original paper yields an estimate that is more reliable than previously thought, at least for protein families that span numerous, independently evolving taxa. Finally, Matlock and Swamidass have not provided any data whatsoever to falsify my hypothesis stated earlier. The scientific evidence, therefore, from actual data available on Pfam, suggests that the information required to code for protein families is statistically very significant and, thus, tests positive for an intelligent source. More.

But surely theistic evolution can accomplish all things, no?

Formal review here.

See also: Kirk Durston: Earth most special planet after all?

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Comments
GIGO is real. And in the world of evolutionary simulations, pervasive. The question is not whether we can write a simulation that produces some evolutionary-favorable outcome. The question is whether our beloved simulation bears any realistic relationship to reality. If it doesn't, it is nonsense. (Avida, you know who you are.) Glad Durston is challenging the simplistic, naive, materialist claims. And gpuccio, of course. :)Eric Anderson
April 5, 2017
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gpuccio, Thank you for reminding us about what you wrote on this topic.Dionisio
April 5, 2017
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Dionisio: I believe I recently wrote a few comments about that paper, which are, IMO, in perfect accord with what Durston says here. :) Here: https://uncommondescent.com/intelligent-design/the-amazing-level-of-engineering-in-the-transition-to-the-vertebrate-proteome-a-global-analysis/#comment-627489 And following, up to comment #17.gpuccio
April 5, 2017
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Dionisio: interesting topic Yeahmike1962
April 5, 2017
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interesting topicDionisio
April 4, 2017
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