Re: Science = 100% falsifiability? Really?

On Dec 23, 5:02 am, Rupert Morrish <rup...@xxxxxxxxxxx> wrote:
Seanpit wrote:
On Dec 20, 4:55 pm, Rupert Morrish <rup...@xxxxxxxxxxx> wrote:
As Einstein put it, what is most amazing about the universe is that it
actually make sense to us. It doesn't have to you know.
Evolution makes sense to me, and almost everyone who actually studies
living organisms.

Ah yes, and what is your educational background?

BA in Mathematics from Cambridge. Not that it's relevant. Perhaps you
missed that my statement does not imply that I study living organisms?

And, where are your
examples of evolution in action producing any novel system of function
that requires a minimum of more than 1000 fairly specified amino acid
residues working at the same time? There are a lot of lower-level
examples - but none beyond this minimum structural threshold
requirement. Why not? Can you make sense of this fact?

How do I measure the number of "fairly specified" residues? How do I
determine the minimum number required for a function?

Doesn't matter. It is quite clear, for the only protein for which
Sean actually declares that it meets all his requirements, cytochrome
c (it has a "minimum threshold size" of about 100 aa's and a "sequence
specificity", based on the ratio of sequences with cytochrome c
function and all sequences of 100 aa's, of 30.7% fully specified or
invariant aa sites to 69.3% fully free to vary sites), that his
"average gap size" is 30.7 aa's. That is the mathematical equivalent
of saying that the "average gap size" is, for a protein like
cytochrome c, the mathematical equivalent of constructing a protein
30.7 aa's long by chance alone. Aka, the '747 in a tornado' strawman
version of evolution modified to only the invariant sites (actually,
the mathematical equivalent of all these sites if the protein were
composed of only completely invariant and completely free to vary
sites) in a protein.

He has not explained yet how this *total* number of mathematically
equivalents of invariant sites is the "average gap size". How is it
"average"? How is it "gap size", which Sean calls the distance
between 'functional sequences'?

The model of sequence space that is used (the only one that fits the
caluculation) to calculate this so-called "average gap size" assumes
that *each* "cytochrome c function" sequence randomly distributed in
some total sequence space is surrounded by 10^40 "non-cytochrome c
function" sequences. But even Sean would admit that such a model of
completely random sequence space is nonsense and the one he *claims*
to be the real one thus differs from the one he uses to calculate
"average gap size" (aka, the number of invariant aa's that must be
assembled completely at random).

The model he actually describes as "sequence space" is one where
cytochrome c function sequences are clustered because they have
sequence and structural similarity. But such a sequence space would
imply that sequences close in structure/sequence to cytochrome c are
clustered nearby. These related sequences would lack the *specified*
function of cytochrome c, yet have *very similar* sequences with most
or part of the function of cytochrome c (such as heme binding) without
having the specified function. However, in the sequence space that
Sean describes, he mathematically assumes tht all the sequences that
do not have the specified function are randomly distributed in an
ocean of 'non-functional' sequences.

The best description of Sean's numbers are that they are GIGO
numerology, numbers that are meaningless but which he uses because
they are the right size for his current needs.

Sean Pitman
www.DetectingDesign.com

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