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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...

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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

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TandTRAQ: an open-source tool for integrated protein identification and quantitation.

Ted Laderas1, Cory Bystrom, Debra McMillen

  • 1Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu

Bioinformatics (Oxford, England)
|September 27, 2007
PubMed
Summary

TandTRAQ is a new tool that combines protein identification and quantification data. This utility integrates results from i-Tracker and X?Tandem, simplifying proteomic analysis pipelines.

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Last Updated: Jul 11, 2026

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
07:38

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Published on: April 11, 2019

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:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Integrating qualitative protein identification with quantitative protein analysis presents challenges due to incompatible output formats.
  • Existing tools often require manual data merging, increasing complexity and potential for error.

Purpose of the Study:

  • To develop a standalone utility, TandTRAQ, for seamless integration of protein identification and quantification data.
  • To facilitate automated data processing within proteomic analysis pipelines.

Main Methods:

  • TandTRAQ integrates results from i-Tracker (an open-source iTRAQ quantitation program) with search results from X?Tandem (an open-source proteome search engine).
  • The utility operates via the command-line, enabling easy integration into automated workflows.

Main Results:

  • TandTRAQ successfully merges qualitative protein identification data with quantitative protein analysis results.
  • The command-line interface allows for straightforward automation and pipeline integration.

Conclusions:

  • TandTRAQ addresses the non-trivial challenge of integrating disparate proteomic data formats.
  • This utility enhances the efficiency and automation capabilities of proteomic data analysis.