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Related Concept Videos

X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal crystal...
X-ray Crystallography02:18

X-ray Crystallography

The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
Determination of Crystal Structures01:29

Determination of Crystal Structures

In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...

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Related Experiment Video

Updated: May 11, 2026

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
07:11

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

Published on: March 22, 2019

Automatic processing of macromolecular crystallography X-ray diffraction data at the ESRF.

Stéphanie Monaco1, Elspeth Gordon, Matthew W Bowler

  • 1Structural Biology Group, European Synchrotron Radiation Facility, 6 rue Jules Horowitz, 38043, Grenoble, France.

Journal of Applied Crystallography
|May 18, 2013
PubMed
Summary
This summary is machine-generated.

Automated data processing pipelines streamline macromolecular crystallography (MX) data collection at synchrotrons. This system rapidly processes diffraction data, aiding decision-making and enabling faster scientific discovery.

Keywords:
automationcomputer programsdata processingmacromolecular crystallography

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Area of Science:

  • Structural Biology
  • Biophysics
  • Crystallography

Background:

  • Automated high-intensity macromolecular crystallography (MX) beamlines increase sample throughput.
  • Rapid X-ray detector technology allows complete datasets in under a minute.
  • High-speed data collection generates large volumes, challenging manual processing.

Purpose of the Study:

  • To develop an automated data reduction pipeline for MX users at the European Synchrotron Radiation Facility (ESRF).
  • To facilitate rapid, automatic processing of MX diffraction data from single or multiple crystals and positions.
  • To provide a fast and reliable alternative to manual data processing at the beamline.

Main Methods:

  • Integration of standard integration and data analysis programs into the ESRF computing environment.
  • Development of a system for rapid automatic processing of MX diffraction data.
  • Storage and intuitive display of results in the ISPyB database for download.

Main Results:

  • A functional automated data reduction pipeline for MX data has been successfully implemented at ESRF.
  • The system handles data from single and multiple positions on single or multiple crystals.
  • Processed data is stored in ISPyB, with potential for automatic experimental phase determination.

Conclusions:

  • Automated pipelines are essential for managing high-throughput MX data.
  • The developed system enhances efficiency and aids decision-making in crystallography experiments.
  • This facilitates faster scientific discovery by providing rapid access to processed data and insights.