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

Published on: November 15, 2017

A partial set covering model for protein mixture identification using mass spectrometry data.

Zengyou He1, Can Yang, Weichuan Yu

  • 1School of Software, Dalian University of Technology, Dalian, China. zyhe@dlut.edu.cn

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|January 15, 2011
PubMed
Summary

This study introduces a new Partial Set Covering (PSC) algorithm for identifying proteins in mixtures using mass spectrometry (MS) data. The method improves accuracy and integrates both MS and MS/MS data for enhanced proteome research.

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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

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

Published on: November 15, 2017

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Protein identification is crucial for mass spectrometry (MS)-based proteome research.
  • Current MS-based methods offer wide coverage but lower accuracy compared to MS/MS methods.
  • There is a need for advanced algorithms to improve protein identification accuracy using MS data.

Purpose of the Study:

  • To extend Peptide Mass Fingerprinting (PMF) for identifying proteins within mixtures.
  • To develop sophisticated algorithms for accurate protein identification from MS data.
  • To create a unified model integrating both MS and MS/MS data for improved proteome analysis.

Main Methods:

  • Formulated protein mixture identification as a Partial Set Covering (PSC) problem.
  • Developed and presented efficient algorithms to solve the PSC problem.
  • Extended the PSC model to accommodate MS/MS data and combined MS/MS and MS data.

Main Results:

  • The proposed PSC-based method significantly outperforms previous MS-based approaches.
  • The method demonstrates utility in enhancing MS/MS-based protein inference.
  • A unified model combining MS and MS/MS data leads to further improvements in identification performance.

Conclusions:

  • The developed PSC algorithms offer a significant advancement in protein mixture identification using MS data.
  • This approach enhances protein inference from MS/MS data and provides a unified framework for integrating different MS data types.
  • The findings pave the way for more accurate and comprehensive proteome research.