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

Gas Chromatography–Mass Spectrometry (GC–MS)01:14

Gas Chromatography–Mass Spectrometry (GC–MS)

7.0K
Gas chromatography–mass spectrometry (GC–MS) is the combination of analytical techniques of gas chromatography and mass spectrometry in a single instrument for analyzing a mixture of compounds. The gas chromatograph separates the compounds in the mixture, and the mass spectrometer analyzes each compound separately to determine the molecular masses and molecular structures.
A gas chromatograph consists of a long, narrow capillary column with a polysiloxane coating on the inner wall....
7.0K
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

2.7K
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...
2.7K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

1.9K
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
1.9K
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

7.1K
Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
7.1K
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

9.1K
Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass. One common type of ionization, known as electron ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave behind a...
9.1K
Mass Spectrometers01:16

Mass Spectrometers

9.2K
This lesson details the instrumentation of a mass spectrometer—a physical instrument to perform mass spectrometry on analyte molecules and record the characteristic mass spectra. This is achieved via three chief functions:
9.2K

You might also read

Related Articles

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

Sort by
Same author

Amino acid-based biological age clock and its implications for human health and aging.

Nature communications·2026
Same author

Sex-Specific Regulation of Glycemic Homeostasis by Theabrownin from Pu-erh Tea.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Gut-derived hyodeoxycholate reprograms the spleen-eye immunometabolic axis to suppress autoimmune uveitis.

Cell death and differentiation·2026
Same author

S'Wipe: user-friendly stool collection for high-throughput gut metabolomics and multi-omics.

mSystems·2026
Same author

Trump, Coca-Cola and the fructose frenzy that influences brain and neuronal tumor development.

Cell death and differentiation·2026
Same author

Targeting the origins of multiple myeloma along hematopoietic stem cell lymphoid lineage differentiation.

Science translational medicine·2025

Related Experiment Video

Updated: Feb 20, 2026

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes
08:23

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Published on: August 6, 2018

12.0K

ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography-High-Resolution Mass

Aleksandr Smirnov1, Wei Jia2, Douglas I Walker3

  • 1University of North Carolina at Charlotte , Charlotte, North Carolina 28223, United States.

Journal of Proteome Research
|October 28, 2017
PubMed
Summary
This summary is machine-generated.

ADAP-GC 3.2 enhances gas chromatography-mass spectrometry (GC-MS) metabolomics by improving user-friendliness and spectral deconvolution. This updated workflow processes complex data more efficiently for metabolite identification.

Keywords:
compound identificationcompound quantitationcomputational work flowgas chromatographyhigh mass resolutionmass spectrometrymetabolomicssoftwarespectral deconvolutionvisualization

More Related Videos

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
10:14

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

5.5K
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

11.0K

Related Experiment Videos

Last Updated: Feb 20, 2026

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes
08:23

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Published on: August 6, 2018

12.0K
Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
10:14

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

5.5K
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

11.0K

Area of Science:

  • Metabolomics
  • Computational chemistry
  • Analytical chemistry

Background:

  • Untargeted gas chromatography-mass spectrometry (GC-MS) metabolomics generates complex data requiring robust computational workflows.
  • Accurate deconvolution of coeluting analytes is crucial for reliable metabolite identification in GC-MS data.
  • Previous versions of the Automated Data Analysis Pipeline for Gas Chromatography (ADAP-GC) lacked user-friendliness.

Purpose of the Study:

  • To develop a more user-friendly version of the ADAP-GC workflow (ADAP-GC 3.2).
  • To improve the speed and accuracy of spectral deconvolution for coeluting analytes.
  • To enable ADAP-GC to process high mass resolution data.

Main Methods:

  • Replaced R-based algorithms with Java analogues integrated into MZmine 2 for improved usability.
  • Implemented DBSCAN clustering for faster spectral deconvolution, replacing hierarchical clustering.
  • Incorporated algorithms for extracted ion chromatogram (EIC) construction and peak detection from LC-MS data.

Main Results:

  • ADAP-GC 3.2 demonstrates enhanced user-friendliness compared to ADAP-GC 3.0.
  • The DBSCAN algorithm provides faster spectral deconvolution.
  • The workflow successfully processes high mass resolution data, improving metabolite identification capabilities.
  • Performance evaluation showed comparable or improved identification and quantitation results against other software.

Conclusions:

  • ADAP-GC 3.2 represents a significant usability and performance improvement for GC-MS metabolomics data analysis.
  • The integration of Java, DBSCAN, and LC-MS algorithms enhances spectral deconvolution and data processing capabilities.
  • This updated workflow facilitates more efficient and accurate metabolite profiling from complex GC-MS datasets.