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Chimia (Aarau). 2011;65(1-2):10-3.

Glycoinformatics: data mining-based approaches.

Author information

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

Abstract

Carbohydrates or glycans are major cellular macromolecules, working for a variety of vital biological functions. Due to long-term efforts by experimentalists, the current number of structurally different, determined carbohydrates has exceeded 10,000 or more. As a result data mining-based approaches for glycans (or trees in a computer science sense) have attracted attention and have been developed over the last five years, presenting new techniques even from computer science viewpoints. This review summarizes cutting-edge techniques for glycans in each of the three categories of data mining: classification, clustering and frequent pattern mining, and shows results obtained by applying these techniques to real sets of glycan structures.

PMID:
21469437
[Indexed for MEDLINE]

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