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

MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

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...
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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...
Matrix-Assisted Laser Desorption Ionization (MALDI)01:08

Matrix-Assisted Laser Desorption Ionization (MALDI)

Matrix-assisted laser desorption ionization (MALDI) is a powerful analytical technique used in mass spectrometry. It enables the identification and characterization of various biomolecules, including proteins, peptides, nucleic acids, and carbohydrates. MALDI is an ionization technique, widely employed in biological and medical research, as well as in fields like pharmacology and biochemistry.The analyte of interest, a biomolecule or a mixture of biomolecules, is mixed with a suitable matrix...
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

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...
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

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...
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

You might also read

Related Articles

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

Sort by
Same author

Metabolomics across scales: from single cells to population studies.

Nature·2026
Same author

Systematic analyses of lipid mobilization by human lipid transfer proteins.

Nature·2026
Same author

Spatial metabolomics and multiomics integration for breakthroughs in precision medicine for kidney disease.

Nature reviews. Nephrology·2025
Same author

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format.

Journal of proteome research·2025
Same author

HT SpaceM: A high-throughput and reproducible method for small-molecule single-cell metabolomics.

Cell·2025
Same author

Enrichment analysis for spatial and single-cell metabolomics accounting for molecular ambiguity.

Bioinformatics advances·2025
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: May 16, 2026

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)
10:47

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Published on: March 24, 2016

MALDI imaging mass spectrometry: statistical data analysis and current computational challenges.

Theodore Alexandrov1

  • 1Center for Industrial Mathematics, University of Bremen, Bibliothekstr, 1, 28359 Bremen, Germany. theodore@uni-bremen.de

BMC Bioinformatics
|November 27, 2012
PubMed
Summary
This summary is machine-generated.

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry offers label-free, spatially-resolved chemical analysis. This paper details computational methods for analyzing MALDI-imaging data, focusing on multivariate statistics for biomarker discovery.

More Related Videos

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models
08:14

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models

Published on: December 5, 2014

Related Experiment Videos

Last Updated: May 16, 2026

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)
10:47

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Published on: March 24, 2016

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models
08:14

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models

Published on: December 5, 2014

Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry (MALDI-imaging) is a label-free technique for spatially-resolved chemical analysis.
  • It is widely used for diverse sample types, including biological tissues and thin films, with significant advancements in the last decade.
  • MALDI-imaging is a powerful tool in biochemistry and chemical analysis.

Purpose of the Study:

  • To outline computational methods for analyzing MALDI-imaging data.
  • To emphasize multivariate statistical approaches, discussing their advantages and disadvantages.
  • To provide recommendations for applying these methods and discuss challenges in statistical analysis.

Main Methods:

  • Focus on multivariate statistical methods for MALDI-imaging data analysis.
  • Elucidation of unsupervised data mining and supervised classification methods for biomarker discovery.
  • Presentation of a high-throughput computational pipeline for MALDI-imaging data interpretation using spatial segmentation.

Main Results:

  • Discussion of the pros and cons of various computational methods for MALDI-imaging data analysis.
  • Explanation of techniques for biomarker discovery using statistical approaches.
  • Introduction of a pipeline for efficient interpretation of complex MALDI-imaging datasets.

Conclusions:

  • Computational methods, particularly multivariate statistics, are crucial for interpreting MALDI-imaging data.
  • Advanced statistical techniques enable biomarker discovery and spatial analysis.
  • Addressing current challenges in statistical analysis is key for the future of MALDI-imaging.