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Related Concept Videos

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...
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...
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 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...
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 dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data.

Penghao Wang1, Pengyi Yang, Jonathan Arthur

  • 1School of Mathematics and Statistics, University of Sydney, Sydney, Australia. penghao.wang@sydney.edu.au

Bioinformatics (Oxford, England)
|July 15, 2010
PubMed
Summary
This summary is machine-generated.

A new wavelet-based algorithm significantly improves peptide and protein identification in mass spectrometry proteomics by enhancing spectra pre-processing. This robust method integrates seamlessly into analysis workflows, boosting discovery rates for researchers.

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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

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Last Updated: Jun 11, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

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Published on: November 15, 2017

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

Area of Science:

  • Proteomics
  • Biotechnology
  • Bioinformatics

Background:

  • Mass spectrometry (MS)-based proteomics is crucial for protein identification and functional characterization in biological and medical research.
  • Effective analysis of MS data, particularly spectra pre-processing, is critical for accurate protein identification.
  • Existing pre-processing algorithms need improvement for robustness and integration into practical workflows.

Purpose of the Study:

  • To develop a novel, robust pre-processing algorithm for mass spectrometry (MS) data.
  • To enhance the identification of peptides and proteins in proteomic analyses.
  • To create an algorithm easily integrated into existing proteomic analysis pipelines.

Main Methods:

  • Developed a new pre-processing algorithm based on wavelet theory.
  • Utilized a dynamic peak model for peak identification in mass spectra.
  • Integrated the algorithm into a complete proteomic analysis workflow.

Main Results:

  • The new algorithm significantly increases peptide and protein identification at a given false discovery rate compared to existing methods.
  • Demonstrated superior performance using a reference library of raw MS and tandem MS spectra.
  • The method is designed for easy integration into proteomic analysis pipelines.

Conclusions:

  • The developed wavelet-based pre-processing algorithm offers a significant advancement in MS data analysis.
  • This method improves the accuracy and efficiency of protein identification in proteomics.
  • The algorithm is readily available and suitable for practical wet-lab applications.