> I find the "super-resolution" claims in this paper a bit of a conjuring
trick.
I think it is understood that information cannot come from nothing. You
cannot cheat in basic physics. Interestingly, I had the same discussion with
bioinformatics colleagues a short time ago. The problem is the same and
seems of a semantic nature. They are using prior information of some sort
(undisclosed) to successfully improve maps and they suggested to call this
'resolution increase'. I had the same objection and said that in
crystallography resolution is a relatively hard term defined by the degree
to which experimental observations are available, and as crystallographers
we won't like that claim at all.
On the other side it is uncontested that as long as the model fits
(crossvalidation-) data better when prior information is used, something
useful has been achieved - again with all the caveats of weights and bias
etc admitted.
However, how to entice non-experts to actually use new methods is another
thing, and here the semantics come in. In essence, if at the end it results
in better structures, how much of the unfortunately but undeniably necessary
salesmanship is just right or acceptable? Within contemporary social
constraints (aka Zeitgeist) that remains pretty much an infinitely debatable
matter..
Merry Christmas, BR
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Dear Bernhard,
I must say that I find the "super-resolution" claims in this paper a
bit of a conjuring trick. If the final refined model has greater accuracy
than one would expect from the resolution of the data it has been refined
against, it is because that extra accuracy has been lifted from the higher
resolution data that were used to refine the structure on the basis of which
the elastic network restraints were created.
Should we then say that we achieve super-resolution whenever we refine
a macromolecular structure using Engh & Huber restraints, because these
enable us to achieve distance accuracies comparable with those in the small
molecules structures in the Cambridge Structural Database?
Perhaps I have missed an essential point of this paper.
With best wishes,
Gerard.
