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GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes
BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905134/ https://www.ncbi.nlm.nih.gov/pubmed/29669592 http://dx.doi.org/10.1186/s13326-018-0182-0 |
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author | Solovieva, Elena Shikanai, Toshihide Fujita, Noriaki Narimatsu, Hisashi |
author_facet | Solovieva, Elena Shikanai, Toshihide Fujita, Noriaki Narimatsu, Hisashi |
author_sort | Solovieva, Elena |
collection | PubMed |
description | BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. RESULTS: We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. CONCLUSIONS: Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the metabolism of glycans as well as how this impaired metabolism affects various biological functions and human health. In this way, GGDonto will be useful in fields related to glycoscience, including cell biology, biotechnology, and biomedical, and pharmaceutical research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13326-018-0182-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5905134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59051342018-04-24 GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes Solovieva, Elena Shikanai, Toshihide Fujita, Noriaki Narimatsu, Hisashi J Biomed Semantics Research BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. RESULTS: We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. CONCLUSIONS: Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the metabolism of glycans as well as how this impaired metabolism affects various biological functions and human health. In this way, GGDonto will be useful in fields related to glycoscience, including cell biology, biotechnology, and biomedical, and pharmaceutical research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13326-018-0182-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-18 /pmc/articles/PMC5905134/ /pubmed/29669592 http://dx.doi.org/10.1186/s13326-018-0182-0 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Research Solovieva, Elena Shikanai, Toshihide Fujita, Noriaki Narimatsu, Hisashi GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title | GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title_full | GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title_fullStr | GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title_full_unstemmed | GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title_short | GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
title_sort | ggdonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905134/ https://www.ncbi.nlm.nih.gov/pubmed/29669592 http://dx.doi.org/10.1186/s13326-018-0182-0 |
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