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X-ray Crystallography

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Related Experiment Video

Updated: Dec 27, 2025

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

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

Published on: August 22, 2017

Measuring and using information gained by observing diffraction data.

Randy J Read¹, Robert D Oeffner¹, Airlie J McCoy¹

¹Cambridge Institute for Medical Research, Department of Haematology, University of Cambridge, The Keith Peters Building, Hills Road, Cambridge CB2 0XY, England.

Acta Crystallographica. Section D, Structural Biology

|March 6, 2020

Summary

This summary is machine-generated.

Information gain, measured by Kullback-Leibler divergence, quantifies measurement precision improvements. This criterion aids in selecting data for crystallographic likelihood calculations, especially for weak or poorly measured datasets.

Keywords:

anisotropy diffraction intensities information gain translational noncrystallographic symmetry

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Area of Science:

Crystallography
Data Science
Statistical Analysis

Background:

Likelihood-based crystallographic algorithms rely on accurate data.
Existing methods for handling measurement error approximations fail with weak or poorly measured data.
Data processing trends may hinder future research by omitting original measurements.

Purpose of the Study:

To introduce information gain (Kullback-Leibler divergence) as a criterion for data selection in crystallography.
To establish appropriate information thresholds for different data quality and error handling methods.
To address concerns regarding the deposition of processed crystallographic data.

Main Methods:

Utilizing Kullback-Leibler divergence to quantify information gain from measurements.
Defining information gain as an upper bound for observation contribution to likelihood scores.
Comparing information thresholds for methods with varying approximations of measurement error.

Main Results:

Information gain provides a principled way to omit data in likelihood calculations.
Higher information thresholds are needed for methods with less accurate error approximations.
Processed data without original measurements pose risks for data reuse.

Conclusions:

Information gain is a valuable metric for data selection in crystallographic analyses.
Careful consideration of data processing and deposition is crucial for reproducibility and future research.
The trend of depositing processed-only data requires attention to ensure data integrity.