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Bioinformatics Advance Access published online on March 7, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm090
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Glycan classification with tree kernels

Yoshihiro Yamanishi a,*, Francis Bach b and Jean-Philippe Vert c

aBioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan, bCenter of Mathematical Morphology, Ecole des Mines de Paris, Fontainebleau, France, cCenter for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France

*To whom correspondence should be addressed. Dr. Yoshihiro Yamanishi, E-mail: yoshi{at}kuicr.kyoto-u.ac.jp yoshifrjp{at}yahoo.co.jp


  Abstract

Motivation: Glycans are covalent assemblies of sugar that play crucial roles in many cellular processes. Recently, comprehensive data about the structure and function of glycans have been accumulated, therefore the need for methods and algorithms to analyze these data is growing fast.

Results: This paper presents novel methods for classifying glycans and detecting discriminative glycan motifs with support vector machines (SVM). We propose a new class of tree kernels to measure the similarity between glycans. These kernels are based on the comparison of tree substructures, and take into account several glycan features such as the sugar type, the sugar bound type, or layer depth. The proposed methods are tested on their ability to classify human glycans into four blood components: leukemia cells, erythrocytes, plasma, and serum. They are shown to outperform a previously published method. We also applied a feature selection approach to extract glycan motifs which are characteristic of each blood component. We confirmed that some leukemia-specific glycan motifs detected by our method corresponded to several results in the literature.

Availability: Softwares are available upon request.

Supplementary information: Datasets are available at the following webisite: http://web.kuicr.kyoto-u.ac.jp/supp/yoshi/glycankernel/.

Associate Editor: Prof. Anna Tramontano

Received on December 6, 2006; revised on February 1, 2007; accepted on March 5, 2007

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