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dc.contributor.authorAoki-Kinoshita, Kiyoko F
dc.contributor.authorBolleman, Jerven
dc.contributor.authorCampbell, Matthew P
dc.contributor.authorKawano, Shin
dc.contributor.authorKim, Jin-Dong
dc.contributor.authorLütteke, Thomas
dc.contributor.authorMatsubara, Masaaki
dc.contributor.authorOkuda, Shujiro
dc.contributor.authorRanzinger, Rene
dc.contributor.authorSawaki, Hiromichi
dc.contributor.authorShikanai, Toshihide
dc.contributor.authorShinmachi, Daisuke
dc.contributor.authorSuzuki, Yoshinori
dc.contributor.authorToukach, Philip
dc.contributor.authorYamada, Issaku
dc.contributor.authorPacker, Nicolle H
dc.contributor.authorNarimatsu, Hisashi
dc.date.accessioned2014-01-27T19:29:00Z
dc.date.available2014-01-27T19:29:00Z
dc.date.issued2013-11-26
dc.identifier.citationJournal of Biomedical Semantics. 2013 Nov 26;4(1):39
dc.identifier.urihttp://dx.doi.org/10.1186/2041-1480-4-39
dc.identifier.urihttp://hdl.handle.net/10724/20000
dc.description.abstractAbstract Background Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as “switches” that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases. Results In order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as “proofs-of-concept” to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement. Conclusions We were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains.
dc.titleIntroducing glycomics data into the Semantic Web
dc.typeJournal Article
dc.date.updated2013-12-12T12:22:25Z
dc.description.versionPeer Reviewed
dc.language.rfc3066en
dc.rights.holderKiyoko F Aoki-Kinoshita et al.; licensee BioMed Central Ltd.


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