24 research outputs found

    GlycomeDB—a unified database for carbohydrate structures

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    GlycomeDB integrates the structural and taxonomic data of all major public carbohydrate databases, as well as carbohydrates contained in the Protein Data Bank, which renders the database currently the most comprehensive and unified resource for carbohydrate structures worldwide. GlycomeDB retains the links to the original databases and is updated at weekly intervals with the newest structures available from the source databases. The complete database can be downloaded freely or accessed through a Web-interface (www.glycome-db.org) that provides flexible and powerful search functionalities

    Glycoproteomic and glycomic databases

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    Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research

    Glycoproteomic and glycomic databases

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    A Systematic Framework to Derive N-glycan Biosynthesis Process and the Automated Construction of Glycosylation Networks

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    GlycomicsDB - A Data Integration Platform for Glycans and their Strucutres

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    Glycomics is a discipline of biology that deals with the structure and function of glycans (or carbohydrates). Analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are having a significant impact on the field of glycomics. However, effective progress in glycomics research requires collaboration between laboratories to share experimental data, structural information of glycans, and simulation results. Herein we report the development of a web-based data management system that can incorporate large volumes of data from disparate sources and organize them into a uniform format for users to store and access. This system enables participating laboratories to set up a shared data repository which members of interdisciplinary teams can access. The system is able to manage and share raw MS data and structural information of glycans

    Structural Biology of Glycoproteins

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    Automatic validation of glycan sequences in distributed databases

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    The creation and maintenance of glycan databases is critically important for the development of the field of glycobiology. As part of the process to build up the database, any deposited sequences need to be validated to ensure the correctness of the database. This thesis details the design and implementation of a semi-automatic system to validate new sequences with respect to the context that the sequences appear in
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