Impacts of sulphur nutrition on selenium and molybdenum concentrations in wheat grain

Contact: fax: þ441582763010. E-mail address: [email protected] audienc

The glycoconjugate ontology (GlycoCoO) for standardizing the annotation of glycoconjugate data and its application

Recent years have seen great advances in the development of glycoproteomics protocols and methods resulting in a sustainable increase in the reporting proteins, their attached glycans and glycosylation sites. However, only very few of these reports find their way into databases or data repositories. One of the major reasons is the absence of digital standard to represent glycoproteins and the challenging annotations with glycans. Depending on the experimental method, such a standard must be able to represent glycans as complete structures or as compositions, store not just single glycans but also represent glycoforms on a specific glycosylation side, deal with partially missing site information if no site mapping was performed, and store abundances or ratios of glycans within a glycoform of a specific site. To support the above, we have developed the GlycoConjugate Ontology (GlycoCoO) as a standard semantic framework to describe and represent glycoproteomics data. GlycoCoO can be used to represent glycoproteomics data in triplestores and can serve as a basis for data exchange formats. The ontology, database providers and supporting documentation are available online (https://github.com/glycoinfo/GlycoCoO).</p

GlycoRDF : an ontology to standardize glycomics data in RDF

Motivation: Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. Results: An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. Availability and implementation: The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/). Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.7 page(s

Latest developments in Semantic Web technologies applied to the glycosciences

The Integrated Life Science Database Project of Japan funded a group of glycoscientists to carry out a project to integrate glycoscience databases using Semantic Web technologies. As a continuation of the previous project period, the Japan Consortium for Glycobiology and Glycotechnology Database (JCGGDB) developed several glycoscience-related databases. The GlycoProtDB database is among those being integrated, providing an important resource to understand protein glycosylation. Another database being integrated is GlycoEpitope, a comprehensive database of carbohydrate epitopes and antibodies. In the current project period, we started the development of GlyTouCan, the international glycan structure repository providing unique accession numbers to all glycan structures. Although such databases are sufficiently important in and of themselves, their integration with other—omics data such as the protein information in UniProt will be crucial to bring glycosciences to the forefront of life sciences. However, to integrate such disparate sets of data among different fields in a way such that future maintenance costs are minimal, standardized ontologies and formats must be established. Our latest project has attempted to define the minimal standards that are necessary to enable this integration. The technical challenges to integrate all these databases and the technologies to overcome these challenges will be described