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Related Concept Videos

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...
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...
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

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...
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

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 example, the mass of helium...
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...

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Related Experiment Video

Updated: May 27, 2026

Dissecting Multi-protein Signaling Complexes by Bimolecular Complementation Affinity Purification (BiCAP)
06:45

Dissecting Multi-protein Signaling Complexes by Bimolecular Complementation Affinity Purification (BiCAP)

Published on: June 15, 2018

MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and

Laurent Gatto1, Kathryn S Lilley

  • 1Cambridge Centre for Proteomics, Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Tennis Court Road, CB2 1QR, Cambridge, UK. lg390@cam.ac.uk

Bioinformatics (Oxford, England)
|November 25, 2011
PubMed
Summary

MSnbase is an R/Bioconductor package for analyzing quantitative proteomics data using isobaric tagging. It offers a framework for reproducible research, including data import, quality control, visualization, and statistical analysis integration.

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Quantitative proteomics experiments often utilize isobaric tagging for relative quantification.
  • Analysis of complex proteomics datasets requires specialized software tools.
  • The R/Bioconductor ecosystem provides a robust platform for bioinformatics research.

Purpose of the Study:

  • To introduce MSnbase, an R/Bioconductor package designed for the analysis of quantitative proteomics data.
  • To provide a comprehensive framework for reproducible proteomics data analysis.
  • To facilitate the integration of quantitative proteomics data with statistical analysis tools.

Main Methods:

  • MSnbase is implemented in R and available through Bioconductor.
  • The package supports raw data import, quality control, and visualization.
  • It includes functionalities for data processing and quantitation of isobaric tagging proteomics experiments.

Main Results:

  • MSnbase enables exploratory data analysis for reproducible proteomics research.
  • The package allows direct integration of quantitative proteomics data.
  • It leverages Bioconductor's statistical analysis facilities.

Conclusions:

  • MSnbase provides a valuable tool for researchers analyzing quantitative proteomics data.
  • The package enhances reproducibility in proteomics data analysis workflows.
  • It facilitates downstream statistical analysis of proteomics experiments.