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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.
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Gas Chromatography–Mass Spectrometry (GC–MS)

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High-Performance Liquid Chromatography: Types of Detectors01:15

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Related Experiment Video

Updated: May 9, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

Graph-based peak alignment algorithms for multiple liquid chromatography-mass spectrometry datasets.

Jijie Wang1, Henry Lam

  • 1Division of Biomedical Engineering and Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.

Bioinformatics (Oxford, England)
|August 2, 2013
PubMed
Summary
This summary is machine-generated.

LWBMatch is a novel algorithm for aligning liquid chromatography-mass spectrometry maps. It accurately corrects retention time shifts, outperforming existing tools for proteomics data analysis.

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Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
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Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
10:14

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Liquid chromatography coupled to mass spectrometry (LC-MS) is crucial for proteomics.
  • Label-free quantitative proteomics relies on aligning LC-MS maps.
  • Retention time (RT) shifts between experiments pose a significant alignment challenge.

Purpose of the Study:

  • To develop a robust algorithm for aligning LC-MS maps with significant RT shifts.
  • To improve the accuracy and reliability of label-free quantitative proteomics.

Main Methods:

  • Developed LWBMatch, an algorithm using weighted bipartite matching for direct peak-to-peak mapping.
  • Employed locally weighted scatterplot smoothing and a novel voting scheme for large RT shifts.
  • Validated alignment accuracy using tandem mass spectrometry identifications.

Main Results:

  • LWBMatch effectively aligns LC-MS maps even with substantial RT shifts (>500 s).
  • The algorithm demonstrates superior precision and recall compared to existing tools.
  • LWBMatch successfully aligns data acquired on different instruments and settings.

Conclusions:

  • LWBMatch offers a significant advancement in LC-MS data alignment for quantitative proteomics.
  • The method enhances the reliability of proteome-wide comparisons across diverse experimental conditions.
  • LWBMatch is a valuable tool for reproducible and accurate proteomics research.