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 <merr...@uw.edu> 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 > > > > > ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCP4BB&A=1
