Linking crystallographic model and data quality

Karplus, P. Andrew; Diederichs, Kay

Linking crystallographic model and data quality

Dateien

Diederichs linking 208126.pdfGröße: 1.82 MBDownloads: 275

Datum

2012

Autor:innen

Karplus, P. Andrew

Diederichs, Kay

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Biologie

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Science. 2012, 336(6084), pp. 1030-1033. ISSN 0036-8075. eISSN 1095-9203. Available under: doi: 10.1126/science.1218231

Zusammenfassung

In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R merge values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R merge values are poorly suited for determining the high-resolution limit and that current standard protocols discard much useful data. We introduce a statistic that estimates the correlation of an observed data set with the underlying (not measurable) true signal; this quantity, CC*, provides a single statistically valid guide for deciding which data are useful. CC* also can be used to assess model and data quality on the same scale, and this reveals when data quality is limiting model improvement.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Zitieren

ISO 690

KARPLUS, P. Andrew, Kay DIEDERICHS, 2012. Linking crystallographic model and data quality. In: Science. 2012, 336(6084), pp. 1030-1033. ISSN 0036-8075. eISSN 1095-9203. Available under: doi: 10.1126/science.1218231

BibTex

@article{Karplus2012-05-25Linki-20812,
  year={2012},
  doi={10.1126/science.1218231},
  title={Linking crystallographic model and data quality},
  number={6084},
  volume={336},
  issn={0036-8075},
  journal={Science},
  pages={1030--1033},
  author={Karplus, P. Andrew and Diederichs, Kay}
}

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Universitätsbibliographie

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