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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.
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Related Experiment Video

Updated: May 20, 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

MetaboSearch: tool for mass-based metabolite identification using multiple databases.

Bin Zhou1, Jinlian Wang, Habtom W Ressom

  • 1Department of Oncology, Georgetown University, Washington, DC, United States of America.

Plos One
|July 7, 2012
PubMed
Summary
This summary is machine-generated.

Metabolite identification in untargeted metabolomics is enhanced by MetaboSearch, a tool for simultaneous mass-based database searching. It integrates results from multiple databases, improving coverage and chemical identifier information for accurate metabolite discovery.

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

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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

Area of Science:

  • Metabolomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Metabolite identification is crucial in untargeted metabolomics.
  • Current metabolite databases (HMDB, MMCD, Metlin, LIPID MAPS) offer partial coverage.
  • Manual integration of search results from multiple databases is challenging.

Purpose of the Study:

  • To develop a web-based tool for simultaneous mass-based database searching.
  • To integrate and enhance metabolite identification in untargeted metabolomics studies.
  • To improve the comprehensiveness of metabolite coverage and chemical identifier information.

Main Methods:

  • Implemented a web-based software tool, MetaboSearch.
  • Enabled simultaneous mass-based search against four major metabolite databases.
  • Integrated search results using IUPAC International Chemical Identifier (InChI) keys.
  • Accepted ion annotation information for enhanced identification.

Main Results:

  • MetaboSearch provides simultaneous mass-based searching and result integration.
  • The tool retrieves more complete chemical identifier information by cross-referencing databases.
  • Demonstrated improved metabolome coverage and identifier completeness compared to individual databases.
  • Validated on mass spectrometry data from positive and negative ionization modes.

Conclusions:

  • MetaboSearch offers a comprehensive solution for metabolite identification in untargeted metabolomics.
  • The integrated approach significantly improves the depth and accuracy of metabolite discovery.
  • The software enhances the utility of mass spectrometry-based metabolomics studies.