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

Mass Analyzers: Overview01:13

Mass Analyzers: Overview

1.6K
The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
1.6K
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

2.4K
The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
2.4K
Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

2.4K
In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
2.4K
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

2.3K
Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
2.3K
¹H NMR: Pople Notation01:09

¹H NMR: Pople Notation

2.6K
The Pople nomenclature system classifies spin systems based on the difference between their chemical shifts. Coupled spins are denoted by capital letters with subscripts indicating the number of equivalent nuclei. When the coupled nuclei have well-separated chemical shifts, they are assigned letters that are far apart in the alphabet, such as A and X. When the difference in chemical shifts is small, coupled nuclei are named using adjacent letters of the alphabet (AB, MN, or XY).
A proton...
2.6K
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.5K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.5K

You might also read

Related Articles

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

Sort by
Same author

AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.

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

Rational acquisition of laboratory equipment: an accurate mathematical model to estimate the trade-offs in shared and nonshared equipment.

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

Insights from aquaporin structures into drug-resistant sleeping sickness.

eLife·2026
Same author

The Inaugural Flatiron Institute Cryo-EM Conformational Heterogeneity Challenge.

bioRxiv : the preprint server for biology·2025
Same author

Annexin A2 stabilizes the endoplasmic reticulum and actin cytoskeleton and influences the formation of reovirus factories.

Journal of virology·2025
Same author

Merging conformational landscapes in a single consensus space with FlexConsensus algorithm.

Nature methods·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

Related Experiment Video

Updated: Jan 18, 2026

Cryo-EM and Single-Particle Analysis with Scipion
09:06

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

4.4K

How many (distinguishable) classes can we identify in single-particle analysis?

O Lauzirika1, M Pernica2, D Herreros1

  • 1Centro Nacional de Biotecnologia-CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain.

Acta Crystallographica. Section D, Structural Biology
|September 9, 2025
PubMed
Summary
This summary is machine-generated.

Estimating macromolecular structural heterogeneity in cryo-electron microscopy (cryo-EM) is challenging. This study introduces a statistical framework using p-values to accurately determine the number of distinct conformational classes in cryo-EM data.

Keywords:
3D classificationcryo-electron microscopyreproducibility analysisstatistical significancestructural heterogeneity

More Related Videos

Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

9.6K
High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
13:28

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

Published on: May 16, 2017

50.9K

Related Experiment Videos

Last Updated: Jan 18, 2026

Cryo-EM and Single-Particle Analysis with Scipion
09:06

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

4.4K
Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

9.6K
High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
13:28

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

Published on: May 16, 2017

50.9K

Area of Science:

  • Structural biology
  • Biophysics
  • Computational biology

Background:

  • Cryo-electron microscopy (cryo-EM) is crucial for visualizing macromolecular structures.
  • Estimating structural heterogeneity in cryo-EM is vital for understanding biological function but is hindered by particle misclassification and low signal-to-noise ratios.
  • Current methods struggle to resolve subtle structural variations and can blend distinct molecular conformations.

Purpose of the Study:

  • To develop a robust statistical framework for accurately determining the number of distinguishable conformational states in cryo-EM datasets.
  • To address the challenges of particle misclassification and low signal-to-noise ratio in cryo-EM heterogeneity analysis.
  • To provide a method for confidently identifying and quantifying macromolecular structural variability.

Main Methods:

  • Investigated the use of p-values derived from a null hypothesis test.
  • The null hypothesis states that the observed classification of particles is equivalent to a random partition of the dataset.
  • Applied this statistical framework to cryo-EM data to assess the significance of identified structural classes.

Main Results:

  • The proposed p-value approach provides a statistically rigorous method for determining the number of distinct classes in cryo-EM data.
  • This framework helps to overcome limitations posed by noise and potential algorithmic biases in heterogeneity analysis.
  • Successfully demonstrated the utility of p-values in distinguishing true conformational states from random variations.

Conclusions:

  • A novel statistical framework using p-values offers a reliable solution for estimating macromolecular heterogeneity in cryo-EM.
  • This method enhances the accuracy of identifying distinct functional states, improving the biological interpretation of cryo-EM data.
  • The approach provides a critical tool for advancing structural biology research by enabling more precise analysis of structural variability.