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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is formed in...

You might also read

Related Articles

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

Sort by
Same author

Report of high data rate macromolecular crystallography (HDRMX) meeting, 23 July 2025.

Structural dynamics (Melville, N.Y.)·2026
Same author

Conformational flexibility of soybean lipoxygenase is coupled to crystal solvent content in serial crystallography.

bioRxiv : the preprint server for biology·2026
Same author

Tracking the redox reaction of the iron enzyme ribonucleotide reductase using continuous SerialED and SFX.

Structure (London, England : 1993)·2026
Same author

Stabilizing Structural Transitional States between 1- and 2-Dimensional Topologies via Hydrogen Bond-Mediated Crystal Engineering.

Journal of the American Chemical Society·2026
Same author

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science.

Frontiers in high performance computing·2025
Same author

<i>cctbx.xfel</i> : a suite for processing serial crystallographic data.

bioRxiv : the preprint server for biology·2025
Same journal

Structural insights into the synthesis of FMN in prokaryotic organisms.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Native sulfur/chlorine SAD phasing for serial femtosecond crystallography.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Serial crystallographic analysis of protein isomorphous replacement data from a mixture of native and derivative microcrystals.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

The first crystal structure of the peptidase domain of the U32 peptidase family.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Atomic resolution crystal structure of Sapp2p, a secreted aspartic protease from Candida parapsilosis.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Structural characterization of a mitochondrial 3-ketoacyl-CoA (T1)-like thiolase from Mycobacterium smegmatis.

Acta crystallographica. Section D, Biological crystallography·2015
See all related articles

Related Experiment Video

Updated: May 10, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

New Python-based methods for data processing.

Nicholas K Sauter1, Johan Hattne, Ralf W Grosse-Kunstleve

  • 1Physical Biosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA. nksauter@lbl.gov

Acta Crystallographica. Section D, Biological Crystallography
|June 25, 2013
PubMed
Summary
This summary is machine-generated.

New Python frameworks enable rapid analysis of high-volume diffraction data from advanced detectors. This accelerates experiments and data processing at synchrotron light sources and for serial femtosecond crystallography.

Keywords:
cctbxdata processingmultiprocessingreusable code

Related Experiment Videos

Last Updated: May 10, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Area of Science:

  • Crystallography
  • Computational Science
  • Data Analysis

Background:

  • Pixel-array detectors generate extreme data rates (up to 2 TB/h), demanding significant computational resources.
  • Rapid data analysis is crucial for real-time experimental guidance.

Purpose of the Study:

  • To develop and implement high-throughput data analysis frameworks for scientific experiments.
  • To address the computational challenges posed by high-volume diffraction data.

Main Methods:

  • Utilized web-serving tools and Python scripting for data analysis.
  • Implemented a high-throughput Bragg-spot analyzer (cctbx.spotfinder).
  • Developed a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography.

Main Results:

  • Successfully deployed cctbx.spotfinder at multiple synchrotron-radiation beamlines.
  • Enabled efficient data reduction for serial femtosecond crystallography experiments at LCLS.
  • Demonstrated the utility of Python for high-throughput scientific data processing.

Conclusions:

  • Python-based frameworks are effective for managing and analyzing large diffraction datasets.
  • Future work should address complex diffraction patterns, potentially leveraging GPU computing.
  • The developed tools enhance experimental efficiency and data throughput in crystallography.