Development and analysis of web resources using glycoinformatics

Glycans are known to be vital in regard to cell - cell communications and biological development. They are molecules that are synthesized sequentially by enzymes (glycosyltransferases), in contrast to template - based synthesis of nucleic acids and proteins. Currently, glycan - related data obtained by experimental methods are stored in several databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) GLYCAN databases, the Consortium for Functional Glycomics (CFG) and GlycomeDB. Databases have developed independently with individual formats to handle a glycan structure. Therefore it has not been not easy for users to compare the information between databases. Another issue has been that the majority of the algorithms for glycoinformatics research have not been developed as tools, and thus biologists in practice cannot apply their original data to useful algorithms. In present work, in order to enable biologists to utilize these important algorithms for glycoscience research, we have developed two major systems. First, we have develop ed RINGS (Resource for I Nformatics of Glycomes at Soka) which provide s web - based tools for glycan structural analysis that use mathematical and data - mining strategies . I have contributed t o the development of a part of RINGS architectur that links web tool systems and RINGS database . I have also developed two tool systems : Glycan Score Matrix and Glycan Kernel Tool , and two utilities, IUPACtoKCF and GlycoCT{condensed}toKCF . Second, we have developed UniCorn database which stores computationally calculated N - glycans based on the known glycosyltransferase activities of humans. I have collected all of the human glycosyltransferase s related to N - glycan biosynthesis from existing databases including KEGG, GGDB, C AZy, CFG and UniProt. Thereafter, I have developed a system for generating theoretical N - glycans. As a result, we were able to generate over 1 million theoretical N - glycan structures which are saved in UniCorn database. Computational models have been developed to aid the reduc tion of cost and save time for predicting features of glycan structures and synthesis pathways . However, there are gaps between in silico and in vivo studies associated with glycanomics research. In this study, we have filled a major gap in glycosciences by developing the first web resource of data mining tools and algorithms focused on glycan structures as well as developing a comprehensive theoretical N - glycan database. We anticipate that this study will play a key role in filling the gaps between glycobiological analyses in vivo and in silico.