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Mass Spectrometric Analysis of Glycosphingolipid Antigens
13:09

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Published on: April 16, 2013

Complexities and algorithms for glycan sequencing using tandem mass spectrometry.

Baozhen Shan1, Bin Ma, Kaizhong Zhang

  • 1Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada. bxshan@csd.uwo.ca

Journal of Bioinformatics and Computational Biology
|March 8, 2008
PubMed
Summary

Glycan sequencing determines glycan structures crucial for biological events. A new heuristic algorithm and software address the NP-hard problem of de novo glycan sequencing using mass spectrometry data.

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Area of Science:

  • Glycomics
  • Proteomics
  • Computational Biology

Background:

  • Determining glycan structures is essential for understanding diverse biological processes.
  • Glycan sequencing, particularly de novo sequencing, is a critical but challenging task in proteomics.

Purpose of the Study:

  • To address the computational complexity of de novo glycan sequencing.
  • To develop a practical solution for determining unknown glycan structures.

Main Methods:

  • Demonstrated that de novo glycan sequencing is an NP-hard problem.
  • Developed a heuristic algorithm and accompanying software for glycan structure determination.
  • Validated the approach using real-world MS/MS data from glycopeptides.

Main Results:

  • The developed heuristic algorithm provides satisfactory results for practical glycan sequencing.
  • The software enables de novo sequencing without relying on existing glycan databases.

Conclusions:

  • The heuristic approach offers a viable solution for the computationally complex de novo glycan sequencing problem.
  • This work facilitates a deeper understanding of biological events through accurate glycan structure elucidation.