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Peptide Identification Using Tandem Mass Spectrometry01:33

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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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Updated: Sep 11, 2025

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Fast and Memory-Efficient Searching of Large-Scale Mass Spectrometry Data Using Tide.

Attila Kertesz-Farkas1, Frank Lawrence Nii Adoquaye Acquaye1, Vladislav Ostapenko1

  • 1Department of Data Analysis and Artificial Intelligence and Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow 109028, Russia.

Journal of Proteome Research
|August 12, 2025
PubMed
Summary
This summary is machine-generated.

New Tide software significantly speeds up analysis of massive tandem mass spectrometry datasets, handling over 10 million spectra and 7 billion peptides efficiently on standard hardware. This open-source tool offers faster performance with lower memory needs.

Keywords:
Tandem mass spectrometrydatabase searchpeptide detection

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Tandem mass spectrometry (MS/MS) data analysis software has advanced significantly over 30 years.
  • Existing tools face limitations with extremely large datasets (millions of spectra or billions of peptides).

Purpose of the Study:

  • To enhance the Tide search engine for analyzing massive MS/MS datasets.
  • To improve the speed and memory efficiency of large-scale proteomic data processing.

Main Methods:

  • Architectural enhancements to the Tide search engine.
  • Testing on datasets exceeding 10 million spectra and 7 billion peptides.
  • Benchmarking against existing tools like MSFragger and Sage.

Main Results:

  • The enhanced Tide architecture handles >10 million spectra and >7 billion peptides on commodity hardware.
  • Performance is 2-7 times faster than the previous Tide version.
  • Achieves speed comparable to MSFragger and Sage with substantially reduced memory requirements.

Conclusions:

  • The improved Tide engine offers a scalable and efficient solution for large-scale proteomic data analysis.
  • Open-source availability and multi-platform binaries (Windows, Linux, Mac) enhance accessibility.
  • Addresses current limitations in handling massive MS/MS datasets.