Just a note: James Holton said "true B-factor" not "true B-factors".
I believe he was talking about the overall B not the individual B's.
Dale Tronrud
On 3/8/2020 3:25 PM, Rangana Warshamanage wrote:
> Sorry for not being clear enough.
> If B-factors at the end of refinement are the "true B-factors" then they
> represent a true property of data. They should be good enough to assess
> the model quality directly. This is what I meant by B factor validation.
> However, how far are the final B-factors similar to true B-factors is
> another question.
>
> Rangana
>
>
> On Sun, Mar 8, 2020 at 7:06 PM Ethan A Merritt <[log in to unmask]
> <mailto:[log in to unmask]>> wrote:
>
> On Sunday, 8 March 2020 01:08:32 PDT Rangana Warshamanage wrote:
> > "The best estimate we have of the "true" B factor is the model B
> factors
> > we get at the end of refinement, once everything is converged,
> after we
> > have done all the building we can. It is this "true B factor"
> that is a
> > property of the data, not the model, "
> >
> > If this is the case, why can't we use model B factors to validate our
> > structure? I know some people are skeptical about this approach
> because B
> > factors are refinable parameters.
> >
> > Rangana
>
> It is not clear to me exactly what you are asking.
>
> B factors _should_ be validated, precisely because they are refined
> parameters
> that are part of your model. Where have you seen skepticism?
>
> Maybe you thinking of the frequent question "should the averaged
> refined B
> equal the Wilson B reported by data processing?". That discussion usual
> wanders off into explanations of why the Wilson B estimate is or is not
> reliable, what "average B" actually means, and so on. For me the bottom
> line is that comparison of Bavg to the estimated Wilson B is an
> extremely
> weak validation test. There are many better tests for model quality.
>
> Ethan
>
>
>
>
>
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