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MALDI-TOF Mass Spectrometry

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...

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Updated: Nov 9, 2025

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

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

Published on: March 24, 2016

GeenaR: A Web Tool for Reproducible MALDI-TOF Analysis.

Eugenio Del Prete¹, Angelo Facchiano², Aldo Profumo³

¹Institute for Applied Mathematics, National Research Council, Naples, Italy.

Frontiers in Genetics

|April 15, 2021

Summary

GeenaR is a new web tool for analyzing mass spectrometry data. It simplifies processing, analysis, and visualization of MALDI-TOF mass spectra for reproducible research, aiding in cancer biomarker discovery.

Keywords:

cancer analysis mass spectrometry proteomics reproducible research web tool

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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Published on: May 20, 2013

Area of Science:

Proteomics
Analytical Chemistry
Bioinformatics

Background:

Mass spectrometry, particularly MALDI-TOF, is crucial for biological sample characterization.
Analyzing large, noisy mass spectra datasets presents significant computational challenges.
Identifying relevant features for sample characterization requires sophisticated computational methods.

Purpose of the Study:

To introduce GeenaR, a novel web tool for comprehensive MALDI-TOF mass spectra analysis.
To provide a user-friendly platform for pre-processing, analysis, visualization, and comparison of mass spectra.
To support reproducible research through detailed, human-readable reports.

Main Methods:

Development of a web-based tool, GeenaR, offering a complete workflow for MALDI-TOF mass spectra.
Implementation of functionalities for pre-processing, analysis, visualization, and comparison.
Validation of GeenaR using oncological datasets (ovarian and colorectal cancer).

Main Results:

GeenaR provides a user-friendly interface for complex mass spectra analysis.
The tool generates reproducible reports including parameters, results, and processing code.
Successful application demonstrated in analyzing cancer datasets, highlighting its utility in biomarker discovery.

Conclusions:

GeenaR offers a robust and accessible solution for MALDI-TOF mass spectra analysis.
The tool enhances reproducibility in proteomics research.
GeenaR shows promise for applications in cancer research and biomarker identification.