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Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking correspo...

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Detalles Bibliográficos
Autores principales: Chiba, Hirokazu, Nishide, Hiroyo, Uchiyama, Ikuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4395280/
https://www.ncbi.nlm.nih.gov/pubmed/25875762
http://dx.doi.org/10.1371/journal.pone.0122802
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author Chiba, Hirokazu
Nishide, Hiroyo
Uchiyama, Ikuo
author_facet Chiba, Hirokazu
Nishide, Hiroyo
Uchiyama, Ikuo
author_sort Chiba, Hirokazu
collection PubMed
description Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.
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spelling pubmed-43952802015-04-21 Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data Chiba, Hirokazu Nishide, Hiroyo Uchiyama, Ikuo PLoS One Research Article Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis. Public Library of Science 2015-04-13 /pmc/articles/PMC4395280/ /pubmed/25875762 http://dx.doi.org/10.1371/journal.pone.0122802 Text en © 2015 Chiba et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chiba, Hirokazu
Nishide, Hiroyo
Uchiyama, Ikuo
Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title_full Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title_fullStr Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title_full_unstemmed Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title_short Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data
title_sort construction of an ortholog database using the semantic web technology for integrative analysis of genomic data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4395280/
https://www.ncbi.nlm.nih.gov/pubmed/25875762
http://dx.doi.org/10.1371/journal.pone.0122802
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