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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...
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...

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Related Experiment Video

Updated: May 16, 2026

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

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing

Chuan-Le Xiao1, Xiao-Zhou Chen, Yang-Li Du

  • 1Institute of Life and Health Engineering, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Jinan University, Guangzhou 510632, China.

Journal of Proteome Research
|November 21, 2012
PubMed
Summary
This summary is machine-generated.

ProVerB, a novel algorithm for peptide identification, enhances proteomic analysis by utilizing peak intensity information. This method significantly improves peptide identification accuracy and reproducibility in tandem mass spectrometry (LC-MS/MS) data.

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

Area of Science:

  • Proteomics
  • Bioinformatics
  • Analytical Chemistry

Background:

  • Tandem mass spectrometry (LC-MS/MS) is crucial for proteomic analysis.
  • Current peptide identification algorithms primarily rely on peak matching, neglecting peak intensity.
  • Existing methods exhibit limitations in completeness and reproducibility.

Purpose of the Study:

  • To develop a novel peptide identification algorithm, ProVerB.
  • To enhance peptide identification accuracy by incorporating peak intensity information.
  • To improve the reproducibility and confidence of peptide identifications from LC-MS/MS data.

Main Methods:

  • Developed ProVerB, a new algorithm based on a binomial probability distribution model.
  • Incorporated a novel scoring function that utilizes peak intensity information.
  • Evaluated ProVerB against existing algorithms like Mascot, Sequest, and SQID.

Main Results:

  • ProVerB identified significantly more peptides than existing algorithms at a 1% False Discovery Rate (FDR).
  • The algorithm demonstrated enhanced confidence in peptide identifications.
  • ProVerB showed robustness and versatility across various platforms and experimental datasets.

Conclusions:

  • ProVerB offers superior performance in peptide identification from LC-MS/MS data.
  • The algorithm's use of peak intensity information improves accuracy and reproducibility.
  • ProVerB is a versatile, open-source tool for proteomic data analysis.