Publikation: Linking crystallographic model and data quality
Lade...
Dateien
Datum
2012
Autor:innen
Karplus, P. Andrew
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
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.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
570 Biowissenschaften, Biologie
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
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.1218231BibTex
@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}
}RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/20812">
<dcterms:issued>2012-05-25</dcterms:issued>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/20812/1/Diederichs%20linking%20208126.pdf"/>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-11-08T09:20:50Z</dc:date>
<dcterms:bibliographicCitation>Science ; 336 (2012), 6084. - S. 1030-1033</dcterms:bibliographicCitation>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/20812/1/Diederichs%20linking%20208126.pdf"/>
<dc:language>eng</dc:language>
<dc:creator>Diederichs, Kay</dc:creator>
<bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/20812"/>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:contributor>Karplus, P. Andrew</dc:contributor>
<dcterms:title>Linking crystallographic model and data quality</dcterms:title>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-11-08T09:20:50Z</dcterms:available>
<dc:creator>Karplus, P. Andrew</dc:creator>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
<dcterms:abstract xml:lang="eng">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.</dcterms:abstract>
<dc:contributor>Diederichs, Kay</dc:contributor>
<dc:rights>terms-of-use</dc:rights>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
