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

Electrospray Ionization (ESI) Mass Spectrometry01:12

Electrospray Ionization (ESI) Mass Spectrometry

2.6K
Higher molecular weight biomolecules are nonvolatile compounds that may decompose before ionizing or vaporizing during mass analysis with conventional electron impact ionization methods. Accordingly, electrospray ionization (ESI) is the favored method for vaporizing and ionizing biomolecules as it circumvents rapid fragmentation and enables the recording of mass signals for the entire biomolecule.
ESI utilizes electrical energy to transfer ions from the liquid phase of the sample into the...
2.6K
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

5.8K
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...
5.8K
High-Performance Liquid Chromatography: Types of Detectors01:15

High-Performance Liquid Chromatography: Types of Detectors

2.3K
The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte...
2.3K
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

4.1K
An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a soft-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.To...
4.1K
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

2.0K
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...
2.0K
Mass Spectrometers01:16

Mass Spectrometers

9.6K
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:
9.6K

You might also read

Related Articles

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

Sort by
Same author

Phenotypic similarity of adverse drug reactions and disease phenotypes is a bridge to mechanistic discovery.

npj drug discovery·2026
Same author

Integrated flexible DNA methylation-chromatin segmentation modeling enhances epigenomic state annotation.

Nucleic acids research·2026
Same author

Origin of sexual dimorphism in osteoarthritis risk: the impact of pregnancy and parental care.

BMC public health·2026
Same author

Effects of Non-IID Distributions in Lung Cancer Data on Survival Prediction with Federated Ensemble Learning.

Studies in health technology and informatics·2026
Same author

Evaluating the Potential of Machine Learning for Discharge Management on Routine Health Insurance Data.

Studies in health technology and informatics·2026
Same author

Drugst.One DREAM-Drug repurposing through expert annotation and modification.

British journal of pharmacology·2026
Same journal

Lactate Metabolism Dysregulation Drives the Pathogenesis of Acute Kidney Injury.

Metabolites·2026
Same journal

Librarian: An Open-Access Web Application for High-Resolution Mass Spectral Library Assembly.

Metabolites·2026
Same journal

Purine Metabolism Alterations in Patients with Chronic Heart Failure: A Cross-Sectional Study of Associations with Iron Status, Oxidative Stress, and Anemia.

Metabolites·2026
Same journal

The Gut Microbiome in Heart Failure: Pathways to Inflammation and Therapeutic Targets.

Metabolites·2026
Same journal

Metabolic Mechanisms of Hexavalent Chromium-Induced Splenic Immune Injury via Oxidative Stress and Ferroptosis Pathways in New Zealand Rabbits.

Metabolites·2026
Same journal

Improving Speed and Efficiency of DESI Imaging with the Xevo MRT Mass Spectrometer for Analyte Mapping.

Metabolites·2026
See all related articles

Related Experiment Video

Updated: Apr 27, 2026

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments
08:40

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Published on: January 20, 2022

3.8K

Peak detection method evaluation for ion mobility spectrometry by using machine learning approaches.

Anne-Christin Hauschild1, Dominik Kopczynski2, Marianna D'Addario3

  • 1Computational Systems Biology Group, Max Planck Institute for Informatics, Saarbrücken, Germany. jan.baumbach@imada.sdu.dk.

Metabolites
|June 25, 2014
PubMed
Summary
This summary is machine-generated.

Automated peak detection in ion mobility spectrometry (IMS) data is crucial for medical research. Four methods showed similar classification accuracy, with peak model estimation (PME) offering better robustness against overfitting in volatile organic compound analysis.

More Related Videos

Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry
08:56

Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry

Published on: November 22, 2024

1.6K
T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis
16:40

T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis

Published on: July 31, 2010

27.2K

Related Experiment Videos

Last Updated: Apr 27, 2026

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments
08:40

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Published on: January 20, 2022

3.8K
Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry
08:56

Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry

Published on: November 22, 2024

1.6K
T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis
16:40

T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis

Published on: July 31, 2010

27.2K

Area of Science:

  • Analytical Chemistry
  • Biomedical Engineering
  • Computational Biology

Background:

  • Ion mobility spectrometry with multi-capillary columns (MCC/IMS) is an established, inexpensive, and non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs).
  • Its application in metabolomics for medical research requires robust, automated data preprocessing, particularly for patient data classification into groups like healthy or unhealthy.
  • Reliable peak detection without manual intervention is a critical, yet challenging, preprocessing step for machine learning applications in biomarker research.

Purpose of the Study:

  • To evaluate four state-of-the-art automated peak detection methods for MCC/IMS data.
  • To compare the performance of these automated methods against a manually generated gold standard using machine learning classification.
  • To assess the robustness and variance of classification performance concerning perturbations and overfitting.

Main Methods:

  • Evaluation of four automated peak detection algorithms: local maxima search, watershed transformation (IPHex), region-merging (VisualNow), and peak model estimation (PME).
  • Comparison against a manually curated gold standard dataset.
  • Assessment of classification performance using established machine learning methods.
  • Investigation of classification robustness against data perturbations and overfitting.

Main Results:

  • All four automated peak detection methods achieved classification accuracy comparable to the manual gold standard.
  • All evaluated methods, both manual and automatic, demonstrated similar robustness against data perturbations.
  • Peak model estimation (PME) exhibited superior robustness against overfitting in classification performance.

Conclusions:

  • Automated peak detection methods for MCC/IMS data are largely reliable for biomedical applications.
  • While minor differences exist, all evaluated methods facilitate a wide spectrum of real-world applications.
  • Peak model estimation (PME) is recommended for enhanced robustness against overfitting in automated IMS data analysis.