Daisuke Shinmachi

The RINGS Resource for Glycome Informatics Analysis and Data Mining on the Web

In the bioinformatics field, many computer algorithmic and data mining technologies have been developed for gene prediction, protein-protein interaction analysis, sequence analysis, and protein folding predictions, to name a few. This kind of research has branched off from the genomics field, creating the transcriptomics, proteomics, metabolomics, and glycomics research areas in the postgenomic age. In the glycomics field, given the complexity of glycan structures with their branches of monosaccharides in various conformations, new data mining and algorithmic methods have been developed in an attempt to gain a better understanding of glycans. However, these methods have not all been implemented as tools such that the glycobiology community may utilize them in their research. Thus, we have developed RINGS (Resource for INformatics of Glycomes at Soka) as a freely available Web resource for glycobiologists to analyze their data using the latest data mining and algorithmic techniques. It provides a number of tools including a 2D glycan drawing and querying interface called DrawRINGS, a Glycan Pathway Predictor (GPP) tool for dynamically computing the N-glycan biosynthesis pathway from a given glycan structure, and data mining tools Glycan Miner Tool and Profile PSTMM. These tools and other utilities provided by RINGS will be described. The URL for RINGS is http://rings.t.soka.ac.jp/.

GlyTouCan 1.0 – The international glycan structure repository

Glycans are known as the third major class of biopolymers, next to DNA and proteins. They cover the surfaces of many cells, serving as the ‘face’ of cells, whereby other biomolecules and viruses interact. The structure of glycans, however, differs greatly from DNA and proteins in that they are branched, as opposed to linear sequences of amino acids or nucleotides. Therefore, the storage of glycan information in databases, let alone their curation, has been a difficult problem. This has caused many duplicated efforts when integration is attempted between different databases, making an international repository for glycan structures, where unique accession numbers are assigned to every identified glycan structure, necessary. As such, an international team of developers and glycobiologists have collaborated to develop this repository, called GlyTouCan and is available at http://glytoucan.org/, to provide a centralized resource for depositing glycan structures, compositions and topologies, and to retrieve accession numbers for each of these registered entries. This will thus enable researchers to reference glycan structures simply by accession number, as opposed to by chemical structure, which has been a burden to integrate glycomics databases in the past.

Introducing glycomics data into the Semantic Web

BackgroundGlycoscience 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.ResultsIn 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.ConclusionsWe 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.

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/).

GlyTouCan: an accessible glycan structure repository

Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.

e-workflow for recording of glycomic mass spectrometric data in compliance with reporting guidelines

Glycomics targets released glycans from proteins, lipids and proteoglycans. High throughput glycomics is based on mass spectrometry (MS) that increasingly depends on exchange of data with databases and the use of software. This requires an agreed format for accurately recording of experiments, developing consistent storage modules and granting public access to glycomic MS data. The introduction of the MIRAGE (Mimimum Requirement for A Glycomics Experiment) reporting standards for glycomics was the first step towards automating glycomic data recording. This report describes a glycomic e-infrastructure utilizing a well established glycomics recording format (GlycoWorkbench), and a dedicated web tool for submitting MIRAGE-compatible MS information into a public experimental repository, UniCarb-DR. The submission of data to UniCarb-DR should be a part of the submission process for publications with glycomics MSn that conform to the MIRAGE guidelines. The structure of this pipeline allows submission of most MS workflows used in glycomics.

Using GlyTouCan Version 1.0: The First International Glycan Structure Repository

Glycans are known as the third major class of biopolymers next to DNA and proteins and have many biological roles by structural properties. The structure of glycans differs greatly from DNA and proteins in that they are branched structures of monosaccharides, as opposed to linear sequences of amino acids or nucleotides. Therefore, the assignment of glycan structure information has been a difficult problem. In order to solve this problem, an international team of glyco-scientists has collaborated to develop this repository, called GlyTouCan, to provide a centralized resource to deposit glycan structures and obtain unique accession numbers. GlyTouCan can accept glycan structures in any form, including ambiguous structures consisting of compositions and topologies. Users can register new glycan structures and additionally search for glycan structures that have been registered into this repository. All of these tools are freely available at https://glytoucan.org/. This will enable glycomics researchers to easily identify glycan structures by accession number. This chapter describes the procedures for the registration and search methods of glycan structures and provides an overview of the entry pages. Furthermore, troubleshooting tips and cautionary notes for using GlyTouCan are also included.