2013
DOI: 10.1107/s0907444913001121
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Better models by discarding data?

Abstract: In macromolecular X-ray crystallography, typical data sets have substantial multiplicity. This can be used to calculate the consistency of repeated measurements and thereby assess data quality. Recently, the properties of a correlation coefficient, CC 1/2 , that can be used for this purpose were characterized and it was shown that CC 1/2 has superior properties compared with 'merging' R values. A derived quantity, CC*, links data and model quality. Using experimental data sets, the behaviour of CC 1/2 and the … Show more

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Cited by 218 publications
(187 citation statements)
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“…c CC1 ⁄ 2 is the half-data set correlation coefficient (51). d Values for the outer shell are given in parentheses.…”
Section: Resultsmentioning
confidence: 99%
“…c CC1 ⁄ 2 is the half-data set correlation coefficient (51). d Values for the outer shell are given in parentheses.…”
Section: Resultsmentioning
confidence: 99%
“…Values in parentheses are for the highest resolution shell; the data were truncated at I/ (I) > 1.0 (Diederichs & Karplus, 2013 Supplementary Table S1; data-merging statistics are presented in Supplementary Fig. S2 and Supplementary Table S4.…”
Section: Acta Cryst (2017) D73 738-748mentioning
confidence: 99%
“…Further structure refinement and analysis for both crystalline forms are ongoing. 2.1 (36.5) 8.0 (3.5/30.4) † CC 1/2 is the half data-set correlation coefficient (Diederichs & Karplus, 2013). ‡ R merge = P hkl P i jI i ðhklÞ À hIðhklÞij= P hkl jF obs j, where I i (hkl) is the ith intensity measurement of reflection hkl, including symmetry-related reflections, and hI(hkl)i is its average.…”
Section: Data Collection and Processing Of Ctgh43 Crystalsmentioning
confidence: 99%