ArticleActa crystallographica. Section D, Structural biology2017
AUSPEX: a graphical tool for X-ray diffraction data analysis.
Article in Acta crystallographica. Section D, Structural biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Xtricorder: a likelihood-enhanced self-rotation function and application to a machine learning-enhanced Matthews prediction of asymmetric unit copy number.Acta crystallographica. Section D, Structural biology · 2025Article
- Robust and automatic beamstop shadow outlier rejection: combining crystallographic statistics with modern clustering under a semi-supervised learning strategy.Acta crystallographica. Section D, Structural biology · 2024Article
- Advanced exploitation of unmerged reflection data during processing and refinement with autoPROC and BUSTER.Acta crystallographica. Section D, Structural biology · 2024Article
- The CCP4 suite: integrative software for macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2023Article
- 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
- Detecting anomalies in X-ray diffraction images using convolutional neural networks.Expert systems with applications · 2021Article
- Ice in biomolecular cryocrystallography.Acta crystallographica. Section D, Structural biology · 2021Article
- Article
- Identification of the site of oxidase substrate binding in Scytalidium thermophilum catalase.Acta crystallographica. Section D, Structural biology · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
In this paper, AUSPEX, a new software tool for experimental X-ray data analysis, is presented. Exploring the behaviour of diffraction intensities and the associated estimated uncertainties facilitates the discovery of underlying problems and can help users to improve their data acquisition and processing in order to obtain better structural models. The program enables users to inspect the distribution of observed intensities (or amplitudes) against resolution as well as the associated estimated uncertainties (sigmas). It is demonstrated how AUSPEX can be used to visually and automatically detect ice-ring artefacts in integrated X-ray diffraction data. Such artefacts can hamper structure determination, but may be difficult to identify from the raw diffraction images produced by modern pixel detectors. The analysis suggests that a significant portion of the data sets deposited in the PDB contain ice-ring artefacts. Furthermore, it is demonstrated how other problems in experimental X-ray data caused, for example, by scaling and data-conversion procedures can be detected by AUSPEX.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.