Hello Eric,
If it's about PDB, it worked for me a few days ago.
(I used *rsync -rlpt -v -z --delete --port=33444
rsync.rcsb.org::ftp_data/structures/divided/pdb/ /yourfolder*)
Bulat Gabidullin
CMCF, Canadian Light Source
On Fri, Jul 5, 2019 at 10:10 AM Eric Williams
wrote:
> Has anyone
Has anyone successfully accessed the BDB lately? I downloaded the whole
thing by rsync about a year ago, but I am no longer able to do so. I don't
seem to be getting any response from the rsync server at all. If others are
able to access it, I should be looking for a problem on my end. Thanks. :)
Dear Sam,
If you have a P1 space group and your dataset was collected in a single
orientation, you will have a great big gaping cusp in it.
I would suggest that you submit your full dataset to the STARANISO
server at
http://staraniso.globalphasing.org/cgi-bin/staraniso.cgi
You cannot directly compare R-factors because they are calculated over
different sets of data. It's apples and oranges.
Your R-factor gap is a bit large too, perhaps your model can be improved a bit
for instance by using tighter geometric restraints.
Cheers,
Robbie
> -Original
looks like a case of the "if Rfree is lower than 0.300 the structure is
perfect, if Rfree is higher than 0.300 your structure is completely rubbish"
police striking again (some reviewers are like this). A bit like if p is
smaller than 0.05 the effect is definitely real and if p is just about
Well - i would always do the final refinement to the highest resolution
with CC1/2 > 0.5
There may be other problems with the data - completeness low for current
standards ..
Does multiplicity fall off with resolution etc?
Is there considerable anisotropy?
both sets of R factors look
Dear all
Hello again
Thanks a lot for the numerous input.
I received a dataset which was processed to 2.4A but refined to 3A -- this
was the background I raised this question in the first place. Then I looked
at the aimless statistics. At 2.4A the high resolution bin CC1/2 0.626,
I/sigI 2.0,
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Another reason to cut the data (temporarily!) is to avoid discussion later when
you try to publish your model. You need to be able to defend your high
resolution cut-off against the R-merge zealots. The paired refinement test to
find a good resolution cut-off works well for that. It is based on
Dear Graeme,
Right, but you are talking about weights that reflect the data quality and say
nothing about that of the starting model ; however refinement is a comparison
of a model with data.
The higher resolution of the data, the more sensitive they to model
imperfections.
Refinement
Pavel,
Please correct if wrong, but I thought most refinement programs used the
weights e.g. sig(I/F) with I/F so would not really have a hard cut off anyway?
You’re just making the stats worse but the model should stay ~ the same (unless
you have outliers in there)
Clearly there will be a
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