## Data Processing : How Good Are My Data Really?

No Thumbnail Available
##### Files
There are no files associated with this item.
2013
##### Authors
Karplus, P. Andrew
##### Publication type
Contribution to a collection
Published
##### Published in
Advancing Methods for Biomolecular Crystallography / Read, Randy J.; Urzhumtsev, Alexandre G.; Lunin, Vladimir Y. (ed.). - Dordrecht : Springer Netherlands, 2013. - pp. 59-68. - ISBN 978-94-007-6319-7
##### Abstract
Since its inception more than 60 years ago, a “reliability index”, later called “R-value”, has been used to measure the agreement of model and averaged data, and a similar quantity, Rmerge, has been defined to assess the quality of the averaged data. However, a little known fact is that the two kinds of R-values have very different properties and asymptotic behaviors, and cannot be compared with each other. This is the reason that decisions concerning the high-resolution cutoff of data that are based on these R-values are questionable, and also helps explain why disagreements between journal authors and the manuscript reviewers have been so common. Here, the authors will show that a different statistic can be used to overcome these deficiencies, and will establish a direct quantitative relation between data and model quality. This relation is important to judge the extent to which the data are useful, and also gives insight into the quality of the model that is derived from the data. The theoretical and practical consequences are at variance with several commonly employed crystallographic concepts and procedures.
##### Subject (DDC)
570 Biosciences, Biology
##### Keywords
Data quality, Model quality, Resolution, R-value, Rmerge, Rwork, Rfree, Correlation coefficient
##### Cite This
ISO 690DIEDERICHS, Kay, P. Andrew KARPLUS, 2013. Data Processing : How Good Are My Data Really?. In: READ, Randy J., ed., Alexandre G. URZHUMTSEV, ed., Vladimir Y. LUNIN, ed.. Advancing Methods for Biomolecular Crystallography. Dordrecht:Springer Netherlands, pp. 59-68. ISBN 978-94-007-6319-7. Available under: doi: 10.1007/978-94-007-6232-9_6
BibTex
@incollection{Diederichs2013-02-21Proce-38583,
year={2013},
doi={10.1007/978-94-007-6232-9_6},
title={Data Processing : How Good Are My Data Really?},
isbn={978-94-007-6319-7},
publisher={Springer Netherlands},
pages={59--68},
author={Diederichs, Kay and Karplus, P. Andrew}
}

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#" >
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-04-24T11:24:12Z</dc:date>
<dc:creator>Diederichs, Kay</dc:creator>
<dc:creator>Karplus, P. Andrew</dc:creator>
<dc:contributor>Karplus, P. Andrew</dc:contributor>
<dcterms:abstract xml:lang="eng">Since its inception more than 60 years ago, a “reliability index”, later called “R-value”, has been used to measure the agreement of model and averaged data, and a similar quantity, Rmerge, has been defined to assess the quality of the averaged data. However, a little known fact is that the two kinds of R-values have very different properties and asymptotic behaviors, and cannot be compared with each other. This is the reason that decisions concerning the high-resolution cutoff of data that are based on these R-values are questionable, and also helps explain why disagreements between journal authors and the manuscript reviewers have been so common. Here, the authors will show that a different statistic can be used to overcome these deficiencies, and will establish a direct quantitative relation between data and model quality. This relation is important to judge the extent to which the data are useful, and also gives insight into the quality of the model that is derived from the data. The theoretical and practical consequences are at variance with several commonly employed crystallographic concepts and procedures.</dcterms:abstract>
<dc:language>eng</dc:language>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:contributor>Diederichs, Kay</dc:contributor>
<dcterms:issued>2013-02-21</dcterms:issued>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-04-24T11:24:12Z</dcterms:available>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/38583"/>
<dcterms:title>Data Processing : How Good Are My Data Really?</dcterms:title>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
</rdf:Description>
</rdf:RDF>

Yes