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Related Concept Videos

Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

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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...
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Mass Spectrum: Interpretation01:24

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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...
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Tandem Mass Spectrometry01:21

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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...
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Mass Spectrometers01:16

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

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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...
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Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

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The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...
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Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage
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Normalization of mass spectrometry data (NOMAD).

Carl Murie1, Brian Sandri2, Ann-Sofi Sandberg1

  • 1Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.

Advances in Biological Regulation
|November 28, 2017
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Summary

Quantitative proteomics using mass spectrometry (MS) can be biased by experimental runs. We introduce NOMAD, an R package for ANOVA normalization, which effectively removes this bias for more accurate biological sample comparisons.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Quantitative proteomics commonly utilizes iTRAQ and TMT reagent-based mass spectrometry (MS).
  • Multiple MS runs can introduce systematic bias, affecting downstream data analysis.
  • Current reference normalization methods are insufficient for removing this bias.

Purpose of the Study:

  • To address the limitations of existing normalization techniques in quantitative proteomics.
  • To introduce a computationally efficient method for removing MS run bias.
  • To provide a scalable solution for large-scale proteomic datasets.

Main Methods:

  • Development of the NOMAD (normalization of mass spectrometry data) R package.
  • Implementation of a computationally efficient ANOVA normalization approach.
  • Inclusion of protein assembly functionality within the package.

Main Results:

  • NOMAD effectively removes systematic MS run bias, outperforming reference normalization.
  • The ANOVA approach offers superior computational efficiency compared to linear models.
  • NOMAD enables valid comparisons across multiple MS runs, even for large datasets.

Conclusions:

  • NOMAD provides a scalable and effective solution for normalizing quantitative mass spectrometry data.
  • This normalization method improves the accuracy and reliability of proteomic analyses.
  • The R package facilitates robust cross-run comparisons in complex biological studies.