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Cited by 838

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Improved R-factors for diffraction data analysis in macromolecular crystallography

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Diederichs, Kay, Karplus, P. Andrew·1997·Nature Structural Biology

Abstract

The quantity Rsym (also called Rmerge) is almost universally used for describing X-ray diffraction data quality. Here, we prove that Rsym is seriously flawed, because it has an implicit dependence on the redundancy of the data. A corrected R-factor, Rmeas, is introduced as the equivalent robust indicator of data consistency. In addition, we introduce Rmrgd, an R-factor that reflects the gain in accuracy upon averaging of equivalent reflections, as a useful indicator of the quality of reduced data. These new data quality indicators better reveal the benefits of highly redundant data and should stimulate improvements in data quality through increased merging of data from multiple crystals.

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Metadata

Authors
Diederichs, K., & Karplus, P. A.
Venue
Nature Structural Biology
Published
1997-04
Volume
4
Issue
4
Pages
269-275
ISSN
1072-8368 (ISSN-L)
OpenAlex
W1978096114
Cited by
838
References
0
FWCI
9.80
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Improved R-factors for diffraction data analysis in macromolecular crystallography. https://app.cochat.ai/papers/10.1038/nsb0497-269
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Diederichs, K., & Karplus, P. A. (1997). Improved R-factors for diffraction data analysis in macromolecular crystallography. Nature Structural Biology. https://doi.org/10.1038/nsb0497-269

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