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Efficient tree-matching methods for accurate carbohydrate database queries.

Kiyoko F Aoki1, Atsuko Yamaguchi, Yasushi Okuno

  • 1Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. kiyoko@kuicr.kyoto-u.ac.jp

Genome Informatics. International Conference on Genome Informatics
|February 12, 2005
PubMed
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Glycan informatics analyzes tree-structured carbohydrate chains. A new dynamic programming algorithm enables efficient alignment and similarity searching of these complex glycan structures.

Area of Science:

  • Glycomics
  • Bioinformatics
  • Computational Biology

Background:

  • Glycan structures are complex and tree-like, unlike linear sequences.
  • Existing sequence-based algorithms are unsuitable for glycan analysis.
  • There is a need for efficient tools to analyze glycan tree structures.

Purpose of the Study:

  • To develop an accurate and efficient tool for finding and aligning maximally matching glycan trees.
  • To adapt sequence alignment algorithms for tree structures in glycomics.
  • To implement a novel approach for glycan similarity analysis.

Main Methods:

  • Utilized a polynomial-time dynamic programming algorithm for maximum common subtree identification.
  • Developed methods for finding and aligning maximally matching glycan trees.

Related Experiment Videos

  • Employed similarity scores rather than distance metrics for enhanced display of similar trees.

    • Main Results:

    • Successfully implemented an accurate and efficient tool for glycan tree alignment.
    • The developed algorithm is incorporated into the KEGG Glycan database.
    • The method effectively handles the tree structure of glycans for similarity analysis.

    Conclusions:

    • The new algorithm provides a robust solution for glycan informatics challenges.
    • The approach enhances the analysis and comparison of complex glycan structures.
    • This method facilitates better understanding and utilization of glycan data.