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Introducing glycomics data into the Semantic Web. | LitMetric

AI Article Synopsis

  • Glycoscience studies complex carbohydrates (glycans), which play important roles in the functions of proteins and lipids, but current glycomics databases lack connections to other life science databases.
  • Researchers established a standard for representing glycan data using RDF (Resource Description Framework) and created RDF versions of their existing databases to facilitate integration and efficiency in glycomics research.
  • Successful integration allowed for complex queries linking multiple databases, like retrieving data from UniCarbKB and GlycomeDB using SPARQL, thereby enhancing the ability to analyze relationships between proteomics and glycomics.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177142PMC
http://dx.doi.org/10.1186/2041-1480-4-39DOI Listing

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