ArticleActa crystallographica. Section D, Structural biology2020
Making a difference in multi-data-set crystallography: simple and deterministic data-scaling/selection methods.
Article in Acta crystallographica. Section D, Structural biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Evolution of macromolecular crystallography beamlines at the Swiss Light Source and SwissFEL.Journal of synchrotron radiation · 2025Article
- Enhanced intensity-based clustering of isomorphous multi-crystal data sets in the presence of subtle variations.Acta crystallographica. Section D, Structural biology · 2025Article
- Article
- Multimeric structure of a subfamily III haloalkane dehalogenase-like enzyme solved by combination of cryo-EM and x-ray crystallography.Protein science : a publication of the Protein Society · 2023Article
- A robust approach for MicroED sample preparation of lipidic cubic phase embedded membrane protein crystals.Nature communications · 2023Article
- Room-temperature serial synchrotron crystallography of Drosophila cryptochrome.Acta crystallographica. Section D, Structural biology · 2022Article
- Single-support serial isomorphous replacement phasing.Acta crystallographica. Section D, Structural biology · 2022Article
- An automated platform for structural analysis of membrane proteins through serial crystallography.Cell reports methods · 2021Article
- Guidelines for de novo phasing using multiple small-wedge data collection.Journal of synchrotron radiation · 2021Article
- Agonists and allosteric modulators promote signaling from different metabotropic glutamate receptor 5 conformations.Cell reports · 2021Article
- The crystal structure of bromide-boundeLife · 2021Article
- Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phasing by single-wavelength anomalous diffraction (SAD) from multiple crystallographic data sets can be particularly demanding because of the weak anomalous signal and possible non-isomorphism. The identification and exclusion of non-isomorphous data sets by suitable indicators is therefore indispensable. Here, simple and robust data-selection methods are described. A multi-dimensional scaling procedure is first used to identify data sets with large non-isomorphism relative to clusters of other data sets. Within each cluster that it identifies, further selection is based on the weighted ΔCC
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