Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Determination of Crystal Structures01:29

Determination of Crystal Structures

39
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...
39
X-ray Crystallography02:18

X-ray Crystallography

26.6K
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...
26.6K
X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

5.1K
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...
5.1K
Crystallographic Point Groups01:29

Crystallographic Point Groups

36
Crystallographic point groups represent the various symmetry operations that can occur within crystals. They are unique in that at least one point will always remain unchanged during these actions. For instance, consider the triclinic system. This system, devoid of any axis or plane of symmetry, aligns with the C1 and Ci point groups.where Cᵢ is characterized solely by a center of inversion.Contrastingly, the monoclinic system introduces an element of symmetry. This system with one plane...
36

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The TPR2 corepressor forms condensates with repressors to fine-tune growth and development in rice.

The EMBO journal·2026
Same authorSame journal

Miroslav Z. Papiz (1955-2026).

Acta crystallographica. Section D, Structural biology·2026
Same author

Decoding Enzyme-Inhibitor Kinetic Mechanisms by Isothermal Titration Calorimetry: The Case of SARS-CoV-2 3CL<sup>pro</sup>.

Analytical chemistry·2026
Same author

Changes in the structure of mitochondrial processing peptidase driven by adaptation to anaerobiosis.

International journal of biological macromolecules·2026
Same author

Nickel binding shifts Helicobacter pylori HypA toward compact conformations.

Journal of inorganic biochemistry·2026
Same author

Abiotic stress sensing in plants: Biochemical and biophysical basis.

Molecular plant·2026

Related Experiment Video

Updated: Mar 15, 2026

Microcrystallography of Protein Crystals and In Cellulo Diffraction
09:35

Microcrystallography of Protein Crystals and In Cellulo Diffraction

Published on: July 21, 2017

9.6K

Merging of synchrotron serial crystallographic data by a genetic algorithm.

Ulrich Zander1, Michele Cianci2, Nicolas Foos1

  • 1Structural Biology Group, European Synchrotron Radiation Facility, 71 Avenue des Martyrs, 38000 Grenoble, France.

Acta Crystallographica. Section D, Structural Biology
|September 8, 2016
PubMed
Summary

A new genetic algorithm method improves data merging for serial crystallography experiments. This technique enhances data quality for structural biology research by selecting optimal datasets.

Keywords:
cluster analysisgenetic algorithmsserial crystallography

More Related Videos

Structure Solution of the Fluorescent Protein Cerulean Using MeshAndCollect
06:42

Structure Solution of the Fluorescent Protein Cerulean Using MeshAndCollect

Published on: March 19, 2019

6.2K
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

7.4K

Related Experiment Videos

Last Updated: Mar 15, 2026

Microcrystallography of Protein Crystals and In Cellulo Diffraction
09:35

Microcrystallography of Protein Crystals and In Cellulo Diffraction

Published on: July 21, 2017

9.6K
Structure Solution of the Fluorescent Protein Cerulean Using MeshAndCollect
06:42

Structure Solution of the Fluorescent Protein Cerulean Using MeshAndCollect

Published on: March 19, 2019

6.2K
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

7.4K

Area of Science:

  • Structural Biology
  • Crystallography
  • Biophysics

Background:

  • Macromolecular crystallography enables detailed structural analysis of biological molecules.
  • Serial crystallography allows rapid data collection from multiple small crystals, offering advantages like increased dose and in situ data collection.
  • Merging numerous small datasets in serial crystallography presents a significant challenge for data quality.

Purpose of the Study:

  • To develop and evaluate a novel method for selecting optimal datasets in serial crystallography.
  • To improve merging statistics and overall data quality in serial crystallography experiments.

Main Methods:

  • A genetic algorithm was developed and applied to select subsets of data for merging.
  • Five case studies were conducted using the genetic algorithm approach.
  • Merging statistics were compared between the genetic algorithm method and conventional all-data merging.

Main Results:

  • The genetic algorithm successfully identified optimal datasets for merging.
  • Significant improvements in merging statistics were observed compared to conventional methods.
  • The approach demonstrated effectiveness across five diverse case studies.

Conclusions:

  • Genetic algorithms provide an effective computational solution for dataset selection in serial crystallography.
  • This method enhances data quality and reliability in structural studies using serial crystallography.
  • The findings facilitate more efficient and accurate structural determination of biological macromolecules.