title: Mining significant tree patterns in carbohydrate sugar chains.
abstract: BACKGROUND
  Carbohydrate sugar chains or glycans, the third major class of macromolecules, hold branch shaped tree structures. Glycan motifs are known to be two types: (1) conserved patterns called 'cores' containing the root and (2) ubiquitous motifs which appear in external parts including leaves and are distributed over different glycan classes. Finding these glycan tree motifs is an important issue, but there have been no computational methods to capture these motifs efficiently.
  
  
  RESULTS
  We have developed an efficient method for mining motifs or significant subtrees from glycans. The key contribution of this method is: (1) to have proposed a new concept, 'á-closed frequent subtrees', and an efficient method for mining all these subtrees from given trees and (2) to have proposed to apply statistical hypothesis testing to rerank the frequent subtrees in significance. We experimentally verified the effectiveness of the proposed method using real glycans: (1)We examined the top 10 subtrees obtained by our method at some parameter setting and confirmed that all subtrees are significant motifs in glycobiology. (2) We applied the results of our method to a classification problem and found that our method outperformed other competing methods, SVM with three different tree kernels, being all statistically significant.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji 611-0011, Japan.
authors.forename: Kosuke
authors.initials: K
authors.lastname: Hashimoto
authors.forename: Ichigaku
authors.initials: I
authors.lastname: Takigawa
authors.forename: Motoki
authors.initials: M
authors.lastname: Shiga
authors.forename: Minoru
authors.initials: M
authors.lastname: Kanehisa
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Mamitsuka
mesh_terms: D000465:Algorithms; D002240:Carbohydrate Sequence; D002241:Carbohydrates / Q000737:chemistry*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011134:Polysaccharides / Q000737:chemistry*
chemical_list: D002241:Carbohydrates; D011134:Polysaccharides