A Gram Distribution Kernel Applied to Glycan Classification and Motif Extraction

• Published in: Genome Informatics Vol. 17; no. 2; pp. 25 - 34
• Main Authors: Yasuda, Hiroshi, Hirata, Kouichi, Kuboyama, Tetsuji, Aoki(Kinoshita), Kiyoko F., Kashima, Hisashi
• Format: Journal Article
• Language: English
• Published: Japan Japanese Society for Bioinformatics 2006
• Subjects: Algorithms; Amino Acid Motifs; Artificial Intelligence; Biomarkers; Carbohydrate Sequence; Databases, Protein; glycans; Monosaccharides - chemistry; motif extraction; Polysaccharides - analysis; Polysaccharides - chemistry; Polysaccharides - classification; Sequence Analysis, Protein - methods; tree kernel; tree q-grams

We propose a novel general-purpose tree kernel and apply it to glycan structure analysis. Our kernel measures the similarity between two labeled trees by counting the number of common q-length substrings (tree q-grams) embedded in the trees for all possible lengths q. We apply our tree kernel using...