A score matrix to reveal the hidden links in glycans

Motivation: Glycans are the third major class of biomolecules following DNA and proteins. They are extremely vital for the functioning of multicellular organisms. However, comparing the fast development of sequence analysis techniques, informatics work on glycans have a long way to go. Alignment algorithms for glycan tree structures are one of the foremost concerns. In addition, the statistical analysis of these algorithms in terms of biological significance needs to be addressed. Results: We developed a tree-structure alignment algorithm for glycans and performed a statistical analysis of these alignment scores such that biologically interesting features could be captured into a score matrix for glycans. We generated our score matrix in a manner similar to BLOSUM, but with slight variations to accomodate our glycan data, including the incorporation of linkage information. We verified the effectiveness of our new glycan score matrix by illustrating how well the resulting score matrix entries correspond with biological knowledge. Future work for even better improvements with the use of a variety of score matrices for different subclasses of glycans due to their complexity is also discussed.