Publications by authors named "Rene Ranzinger"

Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes.

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Recent technological advances in glycobiology have resulted in a large influx of data and the publication of many papers describing discoveries in glycoscience. However, the terms used in describing glycan structural features are not standardized, making it difficult to harmonize data across biomolecular databases, hampering the harvesting of information across studies and hindering text mining and curation efforts. To address this shortcoming, the Glycan Structure Dictionary has been developed as a reference dictionary to provide a standardized list of widely used glycan terms that can help in the curation and mapping of glycan structures described in publications.

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Glycan microarrays are essential tools in glycobiology and are being widely used for assignment of glycan ligands in diverse glycan recognition systems. We have developed a new software, called Carbohydrate microArray Analysis and Reporting Tool (CarbArrayART), to address the need for a distributable application for glycan microarray data management. The main features of CarbArrayART include: (i) Storage of quantified array data from different array layouts with scan data and array-specific metadata, such as lists of arrayed glycans, array geometry, information on glycan-binding samples, and experimental protocols.

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Recent advances in carbohydrate chemistry, chemical biology, and mass spectrometric techniques have opened the door to rapid progress in uncovering the function and diversity of glycan structures associated with human health and disease. These strategies can be equally well applied to advance non-human health care research. To date, the glycomes of only a handful of non-human, non-domesticated vertebrates have been analyzed in depth due to the logistic complications associated with obtaining or handling wild-caught or farm-raised specimens.

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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.

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Various biological processes at the cellular level are regulated by glycosylation which is a highly microheterogeneous post-translational modification (PTM) on proteins and lipids. The dynamic nature of glycosylation can be studied through metabolic incorporation of non-natural sugars into glycan epitopes and their detection using bio-orthogonal probes. However, this approach possesses a significant drawback due to nonspecific background reactions and ambiguity of non-natural sugar metabolism.

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Summary: Glycoinformatics plays a major role in glycobiology research, and the development of a comprehensive glycoinformatics knowledgebase is critical. This application note describes the GlyGen data model, processing workflow and the data access interfaces featuring programmatic use case example queries based on specific biological questions. The GlyGen project is a data integration, harmonization and dissemination project for carbohydrate and glycoconjugate-related data retrieved from multiple international data sources including UniProtKB, GlyTouCan, UniCarbKB and other key resources.

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Mass spectrometry (MS) is one of the most effective techniques for high-throughput, high-resolution characterization of glycan structures. Although many software applications have been developed over the last decades for the interpretation of MS data of glycan structures, only a few are capable of dealing with the large data sets produced by glycomics analysis. Furthermore, these applications utilize databases that can lead to redundant glycan annotations and do not support post-processing of the data within the software or by third party applications.

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The Minimum Information Required for a Glycomics Experiment (MIRAGE) is an initiative created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to design guidelines that improve the reporting and reproducibility of glycoanalytical methods. Previously, the MIRAGE Commission has published guidelines for describing sample preparation methods and the reporting of glycan array and mass spectrometry techniques and data collections. Here, we present the first version of guidelines that aim to improve the quality of the reporting of liquid chromatography (LC) glycan data in the scientific literature.

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The GLYcan Data Exchange (GLYDE) standard has been developed for the representation of the chemical structures of monosaccharides, glycans and glycoconjugates using a connection table formalism formatted in XML. This format allows structures, including those that do not exist in any database, to be unambiguously represented and shared by diverse computational tools. GLYDE implements a partonomy model based on human language along with rules that provide consistent structural representations, including a robust namespace for specifying monosaccharides.

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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.

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MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26:907-910) and mass spectrometry  data (Kolarich et al.

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The minimum information required for a glycomics experiment (MIRAGE) project was established in 2011 to provide guidelines to aid in data reporting from all types of experiments in glycomics research including mass spectrometry (MS), liquid chromatography, glycan arrays, data handling and sample preparation. MIRAGE is a concerted effort of the wider glycomics community that considers the adaptation of reporting guidelines as an important step towards critical evaluation and dissemination of datasets as well as broadening of experimental techniques worldwide. The MIRAGE Commission published reporting guidelines for MS data and here we outline guidelines for sample preparation.

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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.

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GlycomeDB.

Methods Mol Biol

November 2015

Over the last two decades, several carbohydrate structure databases have been developed and made publicly available by different research groups around the world. This led to the fragmentation of information about carbohydrate structures into different resources that have no or only weak interaction with each other. GlycomeDB was developed to integrate the carbohydrate structures from different resources by generating a single-indexed catalog of these structures that associates each structure with its reference in the original resources.

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The GlycoWorkbench software tool allows users to semiautomatically annotate glycomics MS and MS/MS spectra and MS glycoproteomics spectra. The GlycanBuilder software tool is embedded within GlycoWorkbench allowing users to draw glycan structures and export images of the drawn structures. This chapter demonstrates to users how to draw glycan structures within GlycoWorkbench using the GlycanBuilder software tool.

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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.

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Motivation: In the field of glycomics research, several different techniques are used for structure elucidation. Although multiple techniques are often used to increase confidence in structure assignments, most glycomics databases allow storing of only a single type of experimental data. In addition, the methods used to prepare a sample for analysis is seldom recorded making it harder to reproduce the analytical data and results.

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Most currently available glycan structure databases use their own proprietary structure representation schema and contain numerous annotation errors. These cause problems when glycan databases are used for the annotation or mining of data generated in the laboratory. Due to the complexity of glycan structures, curating these databases is often a tedious and labor-intensive process.

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The MIRAGE (minimum information required for a glycomics experiment) initiative was founded in Seattle, WA, in November 2011 in order to develop guidelines for reporting the qualitative and quantitative results obtained by diverse types of glycomics analyses, including the conditions and techniques that were applied to prepare the glycans for analysis and generate the primary data along with the tools and parameters that were used to process and annotate this data. These guidelines must address a broad range of issues, as glycomics data are inherently complex and are generated using diverse methods, including mass spectrometry (MS), chromatography, glycan array-binding assays, nuclear magnetic resonance (NMR) and other rapidly developing technologies. The acceptance of these guidelines by scientists conducting research on biological systems in which glycans have a significant role will facilitate the evaluation and reproduction of glycomics experiments and data that is reported in scientific journals and uploaded to glycomics databases.

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Background: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis.

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The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data.

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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.

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