ArticleIUCrJ2017
Background modelling of diffraction data in the presence of ice rings.
Article in IUCrJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A versatile nanobody platform for live and super-resolution imaging of synaptic vesicle dynamics and plasticity in rodent and human neurons.Journal of nanobiotechnology · 2026Article
- A previously unrecognized superfamily of macro-conotoxins includes an inhibitor of the sensory neuron calcium channel Cav2.3.PLoS biology · 2023Article
- Article
- Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization.Acta crystallographica. Section D, Structural biology · 2023Article
- A drug-discovery-oriented non-invasive protocol for protein crystal cryoprotection by dehydration, with application for crystallization screening.Journal of applied crystallography · 2022Article
- Detecting ice artefacts in processed macromolecular diffraction data with machine learning.Acta crystallographica. Section D, Structural biology · 2022Article
- Integrated sample-handling and mounting system for fixed-target serial synchrotron crystallography.Acta crystallographica. Section D, Structural biology · 2021Article
- Ice in biomolecular cryocrystallography.Acta crystallographica. Section D, Structural biology · 2021Article
- The crystal structure of AbsH3: A putative flavin adenine dinucleotide-dependent reductase in the abyssomicin biosynthesis pathway.Proteins · 2021Article
- Electron diffraction data processing with DIALS.Acta crystallographica. Section D, Structural biology · 2018Article
- AUSPEX: a graphical tool for X-ray diffraction data analysis.Acta crystallographica. Section D, Structural biology · 2017Article
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Authors and funding
9 authors.
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Abstract
An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye-Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean > 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in
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