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R-factors: Difference between revisions
→what kinds of problems exist with these indicators?
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twin 0.41 0.49 | twin 0.41 0.49 | ||
normal 0.52 0.58 | normal 0.52 0.58 | ||
Another paper which investigates the properties of R-values in the presence of twinning is [http://journals.iucr.org/d/issues/2013/07/00/ba5190/index.html P. R. Evans and G. N. Murshudov (2013) "How good are my data and what is the resolution?" Acta Cryst. (2013). D69, 1204-1214] | Another paper which investigates the properties of R-values in the presence of twinning is [http://journals.iucr.org/d/issues/2013/07/00/ba5190/index.html P. R. Evans and G. N. Murshudov (2013) "How good are my data and what is the resolution?" Acta Cryst. (2013). D69, 1204-1214]. As the title indicates, this paper discusses at what resolution the data should be cut. One important finding is that a perfect model gives an R value of 42.0% (for a perfect twin, 29.1%) against pure noise. This suggests that a model that gives significantly lower R-values in the highest resolution shell may be improved by including higher resolution data. | ||
* R-values and [[pseudo-translation]]: if you have pseudotranslation you should be aware that if you solve the structure by molecular replacement, starting R factors could be 70-80%. | * R-values and [[pseudo-translation]]: if you have pseudotranslation you should be aware that if you solve the structure by molecular replacement, starting R factors could be 70-80%. | ||