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Related Concept Videos

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...
High-Performance Liquid Chromatography: Introduction01:11

High-Performance Liquid Chromatography: Introduction

High-performance liquid chromatography(HPLC), formerly referred to as High-pressure liquid chromatography, is a powerful technique used to separate, identify, and quantify components in complex mixtures. The term "high pressure" refers to using high pressure to push the liquid mobile phase through the tightly packed columns.
In HPLC, two phases play a critical role in the separation process:
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...
High-Performance Liquid Chromatography: Elution Process01:05

High-Performance Liquid Chromatography: Elution Process

In High-Performance Liquid Chromatography (HPLC), the elution process is critical to the separation of analytes and the quality of chromatographic results. Elution describes how compounds move through the column and separate based on their interactions with the mobile and stationary phases. This process determines the resolution, peak shape, and retention times in the chromatogram, which are essential for identifying and quantifying components in complex mixtures. Understanding the elution...
Gas Chromatography–Mass Spectrometry (GC–MS)01:14

Gas Chromatography–Mass Spectrometry (GC–MS)

Gas chromatography–mass spectrometry (GC–MS) is the combination of analytical techniques of gas chromatography and mass spectrometry in a single instrument for analyzing a mixture of compounds. The gas chromatograph separates the compounds in the mixture, and the mass spectrometer analyzes each compound separately to determine the molecular masses and molecular structures.
A gas chromatograph consists of a long, narrow capillary column with a polysiloxane coating on the inner wall. The coating...
High-Performance Liquid Chromatography: Instrumentation00:57

High-Performance Liquid Chromatography: Instrumentation

High-performance liquid chromatography, or HPLC, is an analytical technique that separates liquid samples under high pressures. An HPLC instrument consists of glass bottles for storing solvents called mobile phase reservoirs. HPLC-grade solvents are used to maintain high purity, and the dissolved gases are removed using a degasser, such as a vacuum pumping system or sparging with helium. The solvents are then pumped into the analytical column using a screw-driven syringe or reciprocating pumps.

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Related Experiment Video

Updated: Jun 25, 2026

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
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Published on: February 27, 2020

Two-stage model-based clustering for liquid chromatography mass spectrometry data analysis.

Marta Łuksza1, Bogusław Kluge, Jerzy Ostrowski

  • 1Max Planck Institute for Molecular Genetics. luksza@molgen.mpg.de

Statistical Applications in Genetics and Molecular Biology
|February 19, 2009
PubMed
Summary

This study introduces a new mathematical method for aligning noisy liquid chromatography-mass spectrometry (LC-MS) data, improving biomarker discovery for colorectal cancer diagnostics.

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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
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Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems
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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

Area of Science:

  • Proteomics
  • Biomarker Discovery
  • Computational Biology

Background:

  • Proteomic mass spectrometry is crucial for diagnostics and biological system studies.
  • High-throughput LC-MS data is often noisy and contains errors, necessitating robust data processing.
  • Accurate peak alignment in LC-MS spectra is essential for reliable analysis.

Purpose of the Study:

  • To address the peak alignment challenge in LC-MS spectra.
  • To propose a mathematically sound, model-based clustering approach as an alternative to heuristic methods.
  • To evaluate the effectiveness of the proposed method in identifying statistically significant biomarkers.

Main Methods:

  • Developed a model-based clustering method for LC-MS peak alignment.
  • Modeled experimental errors as deviations from real values.
  • Treated mass spectra as finite Gaussian mixtures, allowing parameter adjustment and quality selection.
  • Investigated and compared different model classes with various constraints.

Main Results:

  • The model-based clustering approach effectively aligned LC-MS spectra.
  • The method facilitated the identification of statistically significant biomarkers.
  • Analysis on plasma samples from colorectal cancer patients and healthy donors demonstrated the method's utility.

Conclusions:

  • Model-based clustering offers a robust solution for LC-MS peak alignment.
  • This approach enhances the reliability of biomarker discovery in proteomics.
  • The method shows promise for improving diagnostic accuracy in diseases like colorectal cancer.