Bridging glycoinformatics and cheminformatics: integration efforts between GlyCosmos and PubChem.

The GlyCosmos Glycoscience Portal (https://glycosmos.org) and PubChem (https://pubchem.ncbi.nlm.nih.gov/) are major portals for glycoscience and chemistry, respectively. GlyCosmos is a portal for glycan-related repositories, including GlyTouCan, GlycoPOST, and UniCarb-DR, as well as for glycan-related data resources that have been integrated from a variety of 'omics databases. Glycogenes, glycoproteins, lectins, pathways, and disease information related to glycans are accessible from GlyCosmos. PubChem, on the other hand, is a chemistry-based portal at the National Center for Biotechnology Information. PubChem provides information not only on chemicals, but also genes, proteins, pathways, as well as patents, bioassays, and more, from hundreds of data resources from around the world. In this work, these 2 portals have made substantial efforts to integrate their complementary data to allow users to cross between these 2 domains. In addition to glycan structures, key information, such as glycan-related genes, relevant diseases, glycoproteins, and pathways, was integrated and cross-linked with one another. The interfaces were designed to enable users to easily find, access, download, and reuse data of interest across these resources. Use cases are described illustrating and highlighting the type of content that can be investigated. In total, these integrations provide life science researchers improved awareness and enhanced access to glycan-related information.

The international glycan repository GlyTouCan version 3.0.

Glycans serve important roles in signaling events and cell-cell communication, and they are recognized by lectins, viruses and bacteria, playing a variety of roles in many biological processes. However, there was no system to organize the plethora of glycan-related data in the literature. Thus GlyTouCan (https://glytoucan.org) was developed as the international glycan repository, allowing researchers to assign accession numbers to glycans. This also aided in the integration of glycan data across various databases. GlyTouCan assigns accession numbers to glycans which are defined as sets of monosaccharides, which may or may not be characterized with linkage information. GlyTouCan was developed to be able to recognize any level of ambiguity in glycans and uniquely assign accession numbers to each of them, regardless of the input text format. In this manuscript, we describe the latest update to GlyTouCan in version 3.0, its usage, and plans for future development.

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).

RDFizing the biosynthetic pathway of E.coli O-antigen to enable semantic sharing of microbiology data.

BACKGROUND: The abundance of glycomics data that have accumulated has led to the development of many useful databases to aid in the understanding of the function of the glycans and their impact on cellular activity. At the same time, the endeavor for data sharing between glycomics databases with other biological databases have contributed to the creation of new knowledgebases. However, different data types in data description have impeded the data sharing for knowledge integration. To solve this matter, Semantic Web techniques including Resource Description Framework (RDF) and ontology development have been adopted by various groups to standardize the format for data exchange. These semantic data have contributed to the expansion of knowledgebases and hold promises of providing data that can be intelligently processed. On the other hand, bench biologists who are experts in experimental finding are end users and data producers. Therefore, it is indispensable to reduce the technical barrier required for bench biologists to manipulate their experimental data to be compatible with standard formats for data sharing. RESULTS: There are many essential concepts and practical techniques for data integration but there is no method to enable researchers to easily apply Semantic Web techniques to their experimental data. We implemented our procedure on unformatted information of E.coli O-antigen structures collected from the web and show how this information can be expressed as formatted data applicable to Semantic Web standards. In particular, we described the E-coli O-antigen biosynthesis pathway using the BioPAX ontology developed to support data exchange between pathway databases. CONCLUSIONS: The method we implemented to semantically describe O-antigen biosynthesis should be helpful for biologists to understand how glycan information, including relevant pathway reaction data, can be easily shared. We hope this method can contribute to lower the technical barrier that is required when experimental findings are formulated into formal representations and can lead bench scientists to readily participate in the construction of new knowledgebases that are integrated with existing ones. Such integration over the Semantic Web will enable future work in artificial intelligence and machine learning to enable computers to infer new relationships and hypotheses in the life sciences.

Development of an integrated and inferenceable RDF database of glycan, pathogen and disease resources.

Glycans are known to play extremely important roles in infections by viruses and pathogens. In fact, the SARS-CoV-2 virus has been shown to have evolved due to a single change in glycosylation. However, data resources on glycans, pathogens and diseases are not well organized. To accurately obtain such information from these various resources, we have constructed a foundation for discovering glycan and virus interaction data using Semantic Web technologies to be able to semantically integrate such heterogeneous data. Here, we created an ontology to encapsulate the semantics of virus-glycan interactions, and used Resource Description Framework (RDF) to represent the data we obtained from non-RDF related databases and data associated with literature. These databases include PubChem, SugarBind, and PSICQUIC, which made it possible to refer to other RDF resources such as UniProt and GlyTouCan. We made these data publicly available as open data and provided a service that allows anyone to freely perform searches using SPARQL. In addition, the RDF resources created in this study are available at the GlyCosmos Portal.