I should clarify.  I am mostly concerned about the electron density map.

I want to make sure that I can most closely compare the maps from two
different quality structures, rather than the datasets themselves via CC1/2
or other metrics.  This is more so for interpreting structural changes.

For example, if there is sparse density for some particular thing
indicating partial occupancy, how can I compare those two maps.  So for
low-resolution datasets, maybe there is less density but is that because of
data quality or because in that dataset there is a lower occupancy through
some meaningful structural change (compared to higher resolution/better
data)?

On Fri, 14 Jun 2024 at 14:16, Matt McLeod <mjmcleo...@gmail.com> wrote:

> Hi all,
>
> I am wondering what the best practice is to compare datasets that are of
> the same protein but different quality, for instance 2 vs. 3 A.
>
> I know that truncating the structures to the same resolution bin is
> alright, but the data quality in the lower resolution bins are also not the
> same.  Is there a way to "inject" noise into the data such that the bins
> are more similar?
>
> These datasets cannot be recollected at higher resolution since they are
> collected at increasingly high pressure, and the resolution change is
> anticorrelated with the pressure; no way to get around crystal stability.
>
> Any suggestions are appreciated,
> Matt
>
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-- 
*Matthew Jordan McLeod, PhD*
*Post-Doctoral Fellow - Cornell University*

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