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Related Experiment Video

Updated: May 13, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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An Efficient Dynamic Programming Algorithm for Phosphorylation Site Assignment of Large-Scale Mass Spectrometry Data.

Fahad Saeed1, Trairak Pisitkun, Jason D Hoffert

  • 1Epithelial Systems Biology Laboratory, National Heart Lung and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland USA.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|March 9, 2013
PubMed
Summary
This summary is machine-generated.

Accurate phosphorylation site assignment in phosphoproteomics is crucial. PhosSA, a new dynamic programming algorithm, achieves >99% accuracy for large-scale tandem mass spectrometry (LC-MS/MS) data, enabling better functional interpretation.

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Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay

Published on: May 3, 2018

Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Phosphorylation site assignment is critical for interpreting phosphoproteomics data.
  • Existing algorithms struggle with accurate site assignment from large-scale LC-MS/MS data.
  • Improved algorithms are needed for reliable functional interpretation.

Purpose of the Study:

  • To develop a novel, accurate, and efficient algorithm for phosphorylation site assignment.
  • To address limitations of current search algorithms in phosphoproteomics.
  • To provide a scalable solution for processing large-scale tandem mass spectrometry data.

Main Methods:

  • A linear-time and linear-space dynamic programming strategy named PhosSA was developed.
  • The algorithm optimizes peak intensities associated with theoretical phosphopeptide fragmentation ions.
  • Quality control is implemented using post-processing criteria for signal-to-noise and spectral redundancy.

Main Results:

  • PhosSA achieves >99% accuracy and high sensitivity in phosphorylation site assignment.
  • The algorithm demonstrates high speed and scalability, processing up to 0.5 million peptides per hour.
  • PhosSA is compatible with various fragmentation (CID, HCD) and labeling (SILAC, iTRAQ) strategies.

Conclusions:

  • PhosSA offers a highly accurate and efficient solution for phosphorylation site assignment in phosphoproteomics.
  • The algorithm's speed and scalability make it suitable for large-scale LC-MS/MS data analysis.
  • PhosSA facilitates more reliable functional interpretation of phosphoproteomics studies.