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Glycoproteomic and glycomic databases
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. Em...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3996109/ https://www.ncbi.nlm.nih.gov/pubmed/24725457 http://dx.doi.org/10.1186/1559-0275-11-15 |
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author | Baycin Hizal, Deniz Wolozny, Daniel Colao, Joseph Jacobson, Elena Tian, Yuan Krag, Sharon S Betenbaugh, Michael J Zhang, Hui |
author_facet | Baycin Hizal, Deniz Wolozny, Daniel Colao, Joseph Jacobson, Elena Tian, Yuan Krag, Sharon S Betenbaugh, Michael J Zhang, Hui |
author_sort | Baycin Hizal, Deniz |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3996109 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer |
record_format | MEDLINE/PubMed |
spelling | pubmed-39961092014-05-01 Glycoproteomic and glycomic databases Baycin Hizal, Deniz Wolozny, Daniel Colao, Joseph Jacobson, Elena Tian, Yuan Krag, Sharon S Betenbaugh, Michael J Zhang, Hui Clin Proteomics Review 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. Springer 2014-04-13 /pmc/articles/PMC3996109/ /pubmed/24725457 http://dx.doi.org/10.1186/1559-0275-11-15 Text en Copyright © 2014 Baycin Hizal et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Baycin Hizal, Deniz Wolozny, Daniel Colao, Joseph Jacobson, Elena Tian, Yuan Krag, Sharon S Betenbaugh, Michael J Zhang, Hui Glycoproteomic and glycomic databases |
title | Glycoproteomic and glycomic databases |
title_full | Glycoproteomic and glycomic databases |
title_fullStr | Glycoproteomic and glycomic databases |
title_full_unstemmed | Glycoproteomic and glycomic databases |
title_short | Glycoproteomic and glycomic databases |
title_sort | glycoproteomic and glycomic databases |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3996109/ https://www.ncbi.nlm.nih.gov/pubmed/24725457 http://dx.doi.org/10.1186/1559-0275-11-15 |
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