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Related Concept Videos

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...
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...
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...
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...
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...

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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

Published on: August 19, 2025

Integrated data management and validation platform for phosphorylated tandem mass spectrometry data.

Anna-Maria Lahesmaa-Korpinen1, Scott M Carlson, Forest M White

  • 1Genome-Scale Biology Program, Institute of Biomedicine, University of Helsinki, Helsinki, Finland.

Proteomics
|September 10, 2010
PubMed
Summary

Automated validation of MS/MS data using phoMSVal significantly reduces false positives in phosphopeptide identification. This platform enhances proteomic analysis accuracy by minimizing manual validation needs.

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Area of Science:

  • Proteomics
  • Bioinformatics
  • Mass Spectrometry

Background:

  • Mass spectrometry/mass spectrometry (MS/MS) is crucial for proteome-wide analysis of protein expression and post-translational modifications (PTMs).
  • Analyzing thousands of MS/MS spectra presents significant downstream challenges, with standard tools like MASCOT yielding high false-positive rates.
  • Manual validation of identified phosphopeptides is often necessary but time-consuming, especially in phosphoproteomics where single peptide assignments support site identification.

Purpose of the Study:

  • To develop an open-source platform, phoMSVal, for automated management and validation of MS/MS data.
  • To improve the accuracy and reduce false positives in identifying phosphopeptides from MS/MS spectra.
  • To provide a reliable tool for enhancing confidence in phosphopeptide assignments.

Main Methods:

  • Development of the phoMSVal platform for MS/MS data management and automated validation.
  • Testing of five classification algorithms with 17 extracted features on over 2600 manually curated spectra.
  • Evaluation of classifier performance using metrics such as Area Under the Curve (AUC) and Positive Predictive Value (PPV).

Main Results:

  • The Naïve Bayes algorithm demonstrated high performance, achieving 97% AUC and 97% PPV for phosphotyrosine data.
  • Using only three features, the Naïve Bayes classifier reduced false positives by 76% compared to MASCOT while retaining 97% of true positives.
  • The method was successfully applied to an independent phosphoserine/threonine dataset, yielding 93% AUC and 91% PPV.

Conclusions:

  • PhoMSVal provides an effective automated solution for validating identified phosphopeptides from MS/MS data.
  • The developed classification algorithms significantly improve accuracy and reduce the need for manual validation in phosphoproteomics.
  • PhoMSVal is broadly applicable to all types of phospho-MS/MS data, enhancing proteomic analysis efficiency and reliability.