title: Glycoinformatics: data mining-based approaches.
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.
authors.affiliation: Kyoto University, Institute for Chemical Research, Bioinformatics Center, Gokasho, Uji 611-0011, Japan. mami@kuicr.kyoto-u.ac.jp
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Mamitsuka
mesh_terms: D002241:Carbohydrates / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D012984:Software
chemical_list: D002241:Carbohydrates