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

NMR Spectroscopy: Spin–Spin Coupling01:08

NMR Spectroscopy: Spin–Spin Coupling

1.3K
The spin state of an NMR-active nucleus can have a slight effect on its immediate electronic environment. This effect propagates through the intervening bonds and affects the electronic environments of NMR-active nuclei up to three bonds away; occasionally, even farther. This phenomenon is called spin–spin coupling or J-coupling. Coupling interactions are mutual and result in small changes in the absorption frequencies of both nuclei involved. While nuclei of the same element are involved...
1.3K
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.0K
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...
1.0K
2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

163
Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other...
163
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

174
Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
174

You might also read

Related Articles

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

Sort by
Same author

Biomimetic Dual-Multivalent Strategy Enabled <i>In Vivo</i> Tumor-Targeted Molecular MRI.

Analytical chemistry·2026
Same author

Generalization of Bleaney's Theory.

The journal of physical chemistry. A·2026
Same author

Long-Term Outcome of Molecularly Defined Oligodendrogliomas: Comparison of Grade 2 and 3 Tumors.

Neurology·2026
Same author

An Enzyme-Responsive Gd(III) MRI Probe for Visualizing β-Hexosaminidase A Activity.

ACS sensors·2026
Same author

Impact of Strut Thickness for Patients Treated With Percutaneous Revascularization for Coronary Bifurcations: Insights From the BIFURCAT-ULTRA Registry.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions·2026
Same author

Who Laughs, and Who Doesn't? Predicting Humor Skills From Personality, Social Anxiety, and Laughter Dispositions of Gelotophobia, Gelotophilia, and Katagelasticism.

Scandinavian journal of psychology·2026
Same journal

Photochemical Pump, Benchtop NMR Probe Spectroscopy for Reaction Monitoring With paraHydrogen.

Magnetic resonance in chemistry : MRC·2026
Same journal

Pulse Programme Considerations for Quantitative NOE Analysis.

Magnetic resonance in chemistry : MRC·2026
Same journal

Assessment of Cryogen-Free NMR as Process Analytical Technology for Chemical Process Understanding Across Field Strengths.

Magnetic resonance in chemistry : MRC·2026
Same journal

ShimNetV2-RM Neural Network for Post-Acquisition Correction of Spectral Lineshapes in NMR Reaction Monitoring.

Magnetic resonance in chemistry : MRC·2026
Same journal

Qualitative and Quantitative Characterization of Isodon rubescens and Its Pharmaceutical Preparations Using NMR and UHPLC-QTOF-MS.

Magnetic resonance in chemistry : MRC·2026
Same journal

Synthesis of <sup>15</sup>N-Labeled Bevirimat Derivatives as Isotopic Chemical Probes of HIV-1 Maturation Inhibition.

Magnetic resonance in chemistry : MRC·2026
See all related articles

Related Experiment Video

Updated: Jun 14, 2025

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments
09:25

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments

Published on: November 1, 2024

1.8K

Extracting Trends From NMR Data With TrAGICo: A Python Toolbox.

Letizia Fiorucci1,2,3, Francesco Bruno1,2, Leonardo Querci1,2

  • 1Centro Europeo di Risonanze Magnetiche, Università degli Studi di Firenze, Sesto Fiorentino, Italy.

Magnetic Resonance in Chemistry : MRC
|June 12, 2025
PubMed
Summary
This summary is machine-generated.

This tutorial introduces TrAGICo, a Python tool for analyzing NMR spectra from Bruker instruments. It simplifies extracting experimental parameters for applications like temperature dependence studies and reaction monitoring.

Keywords:
Pythondata analysisparamagnetic NMRreaction monitoring

More Related Videos

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.3K
15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the &#181;s-ms Timescale
08:09

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Published on: April 19, 2021

5.1K

Related Experiment Videos

Last Updated: Jun 14, 2025

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments
09:25

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments

Published on: November 1, 2024

1.8K
PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.3K
15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the &#181;s-ms Timescale
08:09

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Published on: April 19, 2021

5.1K

Area of Science:

  • Nuclear Magnetic Resonance (NMR) Spectroscopy
  • Computational Chemistry
  • Data Analysis

Background:

  • NMR spectroscopy is crucial for chemical structure elucidation and dynamic studies.
  • Analyzing experimental parameters from NMR spectra can be time-consuming and complex.
  • Automating data extraction enhances efficiency and reproducibility in NMR research.

Purpose of the Study:

  • To present TrAGICo, a Python collection of functions for NMR spectral data analysis.
  • To provide a user-friendly tool for extracting experimental parameters from Bruker NMR data.
  • To demonstrate the utility of TrAGICo in diverse NMR applications.

Main Methods:

  • Development of a Python collection named TrAGICo (Trends Analysis Guided Interfaces Collection).
  • Implementation of functions for extracting parameters from 1D and pseudo-2D NMR spectra.
  • Utilized practical examples to showcase TrAGICo's capabilities.

Main Results:

  • TrAGICo enables efficient extraction of experimental parameters from NMR spectra.
  • Demonstrated successful application in chemical shift temperature dependence analysis.
  • Showcased utility in relaxation studies and reaction monitoring using NMR data.

Conclusions:

  • TrAGICo offers a valuable tool for researchers working with Bruker NMR data.
  • The collection streamlines the analysis of NMR spectra, improving research efficiency.
  • TrAGICo supports a range of NMR applications, facilitating advanced studies.