2013
DOI: 10.1107/s0907444913012274
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Clustering procedures for the optimal selection of data sets from multiple crystals in macromolecular crystallography

Abstract: A systematic approach to the scaling and merging of data from multiple crystals in macromolecular crystallography is introduced and explained.

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Cited by 242 publications
(207 citation statements)
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“…CF 2 data were collected at beamline I24 of the Diamond Light Source and showed quick radiation damage. To obtain a full data set, the first five degrees of data from nine crystals were combined in the Blend program (27) after processing with the XDS package (28). The structure was solved in the Phaser program (29) with a monomer of M, as solved previously (25), as the search model (PDB accession no.…”
Section: Methodsmentioning
confidence: 99%
“…CF 2 data were collected at beamline I24 of the Diamond Light Source and showed quick radiation damage. To obtain a full data set, the first five degrees of data from nine crystals were combined in the Blend program (27) after processing with the XDS package (28). The structure was solved in the Phaser program (29) with a monomer of M, as solved previously (25), as the search model (PDB accession no.…”
Section: Methodsmentioning
confidence: 99%
“…In principle, the ÁCC 1/2 method shares this restriction with the BLEND method (Foadi et al, 2013), which uses a large cell parameter deviation as rejection criterion. However, since it uses the experimental intensity data, the ÁCC 1/2 method directly targets the desired property of optimizing the merged intensity data, and is successful in doing so as seen when being validated.…”
Section: Choice Of Target Function and Rejection Criterionmentioning
confidence: 99%
“…Another method that can be employed is hierarchical clustering of datasets based on their cell parameters (Foadi et al, 2013). This method avoids the problem of false positive rejection of weak datasets, but on the other hand similarity of cell parameters is only a necessary but not a sufficient condition, and does not take similarity of diffraction into account.…”
Section: Introductionmentioning
confidence: 99%
“…Advanced experimental work-flows will enable segments of data collected in different geometries, or from different positions, to be combined to generate the best complete data possible. Software to rank and scale together many independent partial data collections is being developed at several sites (Foadi et al, 2013) and will improve with increasingly refined statistical data models. PX operation modes will be flexible and more integrated with down-stream crystallization platforms, which should soon be able to transfer pre-determined sample coordinates to the beamline for analysis.…”
Section: Perspectivesmentioning
confidence: 99%