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Details

Autor(en) / Beteiligte
Titel
Simulation of small‐angle X‐ray scattering data of biological macromolecules in solution
Ist Teil von
  • Journal of applied crystallography, 2020-04, Vol.53 (2), p.536-539
Ort / Verlag
5 Abbey Square, Chester, Cheshire CH1 2HU, England: International Union of Crystallography
Erscheinungsjahr
2020
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • This article presents IMSIM, an application to simulate two‐dimensional small‐angle X‐ray scattering patterns and, further, one‐dimensional profiles from biological macromolecules in solution. IMSIM implements a statistical approach yielding two‐dimensional images in TIFF, CBF or EDF format, which may be readily processed by existing data‐analysis pipelines. Intensities and error estimates of one‐dimensional patterns obtained from the radial average of the two‐dimensional images exhibit the same statistical properties as observed with actual experimental data. With initial input on an absolute scale, [cm−1]/c[mg ml−1], the simulated data frames may also be scaled to absolute scale such that the forward scattering after subtraction of the background is proportional to the molecular weight of the solute. The effects of changes of concentration, exposure time, flux, wavelength, sample–detector distance, detector dimensions, pixel size, and the mask as well as incident beam position can be considered for the simulation. The simulated data may be used in method development, for educational purposes, and also to determine the most suitable beamline setup for a project prior to the application and use of the actual beamtime. IMSIM is available as part of the ATSAS software package (3.0.0) and is freely available for academic use (http://www.embl‐hamburg.de/biosaxs/download.html). An application is presented to simulate images on an area detector for isotropic small‐angle X‐ray scattering, explicitly accounting for the experimental geometry and yielding radially averaged 1D scattering patterns with statistically appropriate variations.
Sprache
Englisch
Identifikatoren
ISSN: 1600-5767, 0021-8898
eISSN: 1600-5767
DOI: 10.1107/S1600576720000527
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7133063

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