Bill Cole points out a good test for the "FI" hypothesis

Good question. It appears the variations are designed. This is the conclusion I have come up with based on the alpha actin isoforms variation. 4 small variations all getting fixed in populations over long periods of time and across several species with 100% measured conservation.

Rum would have to claim that all 4 got stuck in a local maximum. This is a lot of serendipity to rely on. A optimized designed sequence seems a lot more parsimonious ignoring the philosophical objections.

Let’s avoid speculation and focus on applying @gpuccio’s method as specified, OK?

Up front, your conclusions are wrong. Let’s just walk through the calculation in which you allegedly have so much confidence.

The hypothesis is that sequence conservation represents functional information. Correct?

Sequence conservation shows functional constraint indicates functional information. How many sequences will perform the specific function. If no new sequences are getting fixed in any mammal population then the amount of functional information is certainly high. Could Rum be right and some very different sequence work.

This is questionable as actin interacts with myosin. Maybe so in the unlikely event myosin mutates along with actin so it can escape its fixed position but unless the number of alternative functional sequences is enormous gpuccio’s hypothesis is correct. My original estimate was several hundred orders of magnitude less than the calculated number.

Mutants had lower fitness. That’s it. They functioned worse in comparison to the conserved sequence. It’s trivial.

We already know this is the case merely by looking at variants of the sequence in the human population. As I showed you 8 days ago in this post.

You can’t calculate FI if you have not actually tested unexplored regions of sequence space, because then you don’t know the actual ratio of nonfunctional to functional sequences.

Heck, even for the blatant misapplication of FI Gpuccio has managed to dream up, he’d still have to include every known variant of the protein that exists in all populations, not just the single canonical sequence. If some organism lives with a mutant version without dying and is capable of reproducing, then the sequence is strictly viable, and needs to be included in any calculation that attempts to derive the fraction of sequences that meets the minimal threshold for function. But Gpuccio has not done so.

Also, the “precision” of the method Gpuccio is using to try to gauge the number of sequences that meet the minimal threshold for function is probing so vanishingly small an area of sequence space that any number he comes up with basically commits a hasty generalization fallacy. He simply cannot extrapolate one small area of sequence space to the rest of it when there is zero reason to think the functional and nonfunctional sequences are uniformly distributed in that space.

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You’re just mindlessly declaring this with zero supporting evidence or even any argument to that effect. You haven’t even stated anything that could be taken to imply it. You just write the words and then act as if some sort of fact has been established by that alone.

No, you have not based that on anything. You just say it, that’s it. You type the words into a browser window, that’s what amounts to your “conclusion based on alpha actin isoforms variation”.

And? What’s the problem with that?

No that’s natural selection, not “serendipity”. That’s the whole point of a local optimum: Natural selection drove the sequence up some local peak in the fitness landscape, and it got stuck there because in it’s particular functional context, it is the best one among locally sampled variants. In different contexts with slightly altered interactions, different isoforms represent their own local optimum.

More parsimonious? So that means you have a design model where you are able to quantitatively assess it’s parsimony compared to some evolutionary model? Where have you done this work Bill?

That’s right, nowhere. Ooh, it’s more parsimonious! A claim that you have no idea how to even begin to assess.

Here you’re doing the cargo-cult dance again and using one of those fancy science-sounding words. Want to borrow a lab coat too?

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Bottom line: @colewd has finally made it explicit that he accepts @Mercer’s description of the ID hypothesis: “sequence conservation represents functional information.”

@Mercer, I believe, is now going to help walk Bill thru the calculations necessary to test that hypothesis. I wonder how that will end up?

I predict that Bill will continue to balk at every step because on some conscious level, he has zero confidence in his claim.

Do I get to be a psychiatrist now? :smiley:

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Hypothetically. We’re trying to test that hypothesis. That’s how real science works.

For a cardiac myosin heavy chain, how many sequences have been shown to perform the specific function?

I wish my job was always that easy.

But, hey, let’s not be hasty. Walk him thru the calculations. Someone is bound to learn something, even if Bill doesn’t.

Easier said than done…

So Bill, what is the calculated “FI” for the human beta-cardiac myosin heavy chain?

Keep your hypothesis in mind:

…and think of the most brutal, stringent way to test it, instead of evasions and changing it.

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How did it find the steep hill living in almost infinite sequence in the first place? Now we are seeing 4 steep hills found. Why did natural selection pick four similar but different sequences?

Now your labeling because you have no real explanation for the data.

You’re not looking very carefully.

How many sequences are there that have been shown to “perform the function”?

about 8500 bits.

What is “the function”?

By mutating the ancestral sequence, which you can infer by looking further back in time on the phylogenetic tree of actins.

How did your designer find them? He just dreamt them up?

You’ll have to look at what they are doing to answer that. Why did you designer pick four similar but different sequences?

Natural selection driving function up some local optimum is a real explanation for the data.

This is not a viable explanation. Your kidding yourself.

Different applications. Heart muscle, smooth muscle and aurorta muscle along with the skeletal muscle.

Myosin has very different sequences with these different applications again confirming a different design for a different application. Myosin is highly conserved between species. This is the same thing we saw with the WNT.

Why not? “Because Bill Cole doesn’t think so” isn’t a valid reason.

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He is not arguing from authority. On the contrary, he is pointing out that your vague claim " Search results for cancer in pubmed.gov. If you include mutation its around 200K" doesn’t substantiate either your initial argument or your subsequent (goal post shifted), argument.

By the way, how many papers in Pubmed belong to you or Gil providing evidence for the hypothesis under question? Why don’t either of you do actual science and get published? What’s stopping you?

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I don’t agree as John is constantly arguing from authority. I do agree that stating 1 million papers was not wise and also not necessary to make my point. Thanks for that.

Prove it. When you claim X number of papers in PubMed supports your claim, it looks like you’re arguing from authority, or at least argumentum ad populum. Where are all his arguments from authority?

By the way, how many papers in Pubmed belong to you or Gil providing evidence for the hypothesis under question? Why don’t either of you do actual science and get published? What’s stopping you? Why are you wasting time on a forum when you could reach the scientific world with your evidence?

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