Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

X-ray Crystallography

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...

$X-ray Diffraction of Biological Samples$ 01:10

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...

You might also read

Related Articles

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

Sort by

Same author

Chaperonin recognition of protein dynamics drives drug resistance.

bioRxiv : the preprint server for biology·2026

Same author

Inferring structure factors of weakly populated excited states in perturbative crystallography experiments.

bioRxiv : the preprint server for biology·2026

Same author

AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.

Nature methods·2026

Same author

Sensitive detection of structural dynamics using a statistical framework for comparative crystallography.

Science advances·2025

Same author

AlphaFold as a Prior: Experimental Structure Determination Conditioned on a Pretrained Neural Network.

bioRxiv : the preprint server for biology·2025

Same author

SFCalculator: connecting deep generative models and crystallography.

bioRxiv : the preprint server for biology·2025

Same journal

Scotty: lattice coincidences in the Protein Data Bank.

Acta crystallographica. Section D, Structural biology·2026

Same journal

Scotty: lattice coincidences for macromolecular crystallographic phasing.

Acta crystallographica. Section D, Structural biology·2026

Same journal

Miroslav Z. Papiz (1955-2026).

Acta crystallographica. Section D, Structural biology·2026

Same journal

Structural basis of regioselective double halogenation of the β-carboline tryptoline by the single-component halogenase AetF.

Acta crystallographica. Section D, Structural biology·2026

Same journal

Simulating neutron protein crystallography experiments: applications to the development of the NMX instrument at ESS.

Acta crystallographica. Section D, Structural biology·2026

Same journal

Molecular architecture of the human citrate synthase-malate dehydrogenase 2 metabolon.

Acta crystallographica. Section D, Structural biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 19, 2025

Biochemical and Structural Characterization of the Carbohydrate Transport Substrate-binding-protein SP0092

Biochemical and Structural Characterization of the Carbohydrate Transport Substrate-binding-protein SP0092

Published on: October 2, 2017

Correcting systematic errors in diffraction data with modern scaling algorithms.

Luis A Aldama¹, Kevin M Dalton¹, Doeke R Hekstra¹

¹Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA.

Acta Crystallographica. Section D, Structural Biology

|August 16, 2023

Summary

This summary is machine-generated.

New variational inference methods offer a flexible alternative to traditional least-squares optimization for scaling X-ray diffraction data, improving accuracy in complex structural analyses.

Keywords:

X-ray crystallography deep learning scaling variational inference

More Related Videos

$X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects$

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

Published on: June 8, 2016

$Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene$

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

Published on: August 22, 2017

Related Experiment Videos

Last Updated: Jul 19, 2025

Biochemical and Structural Characterization of the Carbohydrate Transport Substrate-binding-protein SP0092

Biochemical and Structural Characterization of the Carbohydrate Transport Substrate-binding-protein SP0092

Published on: October 2, 2017

$X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects$

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

Published on: June 8, 2016

$Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene$

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

Published on: August 22, 2017

Area of Science:

Materials Science
Crystallography
Data Analysis

Background:

X-ray diffraction is crucial for determining material atomic structures.
Data processing algorithms, particularly scaling, are essential for accurate electron density determination.
Traditional scaling methods use least-squares optimization to correct systematic errors in diffraction intensities.

Purpose of the Study:

To review the history and evolution of X-ray diffraction scaling algorithms.
To introduce and contrast variational inference as a novel approach to data scaling.
To identify use cases and provide guidance for the variational inference algorithm, Careless.

Main Methods:

Review of classical least-squares scaling algorithms.
Introduction to variational inference for simultaneous data merging and error correction.
Application and evaluation of the Careless algorithm.

Main Results:

Variational inference offers a flexible and advantageous alternative to traditional scaling methods.
The Careless algorithm demonstrates the practical application of variational inference in X-ray diffraction.
Specific use cases where variational inference excels have been identified.

Conclusions:

Variational inference presents a powerful new paradigm for X-ray diffraction data scaling.
The Careless algorithm provides a valuable tool for researchers utilizing advanced X-ray sources and experiments.
Future developments in variational scaling methods are anticipated to further enhance structural determination.