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Using Multiple Ontologies to Integrate Complex Biological Data
The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has develop...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447497/ https://www.ncbi.nlm.nih.gov/pubmed/18629202 http://dx.doi.org/10.1002/cfg.498 |
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author | Shimoyama, Mary Petri, Victoria Pasko, Dean Bromberg, Susan Wu, Wenhua Chen, Jiali Nenasheva, Nataliya Kwitek, Anne Twigger, Simon Jacob, Howard |
author_facet | Shimoyama, Mary Petri, Victoria Pasko, Dean Bromberg, Susan Wu, Wenhua Chen, Jiali Nenasheva, Nataliya Kwitek, Anne Twigger, Simon Jacob, Howard |
author_sort | Shimoyama, Mary |
collection | PubMed |
description | The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease. |
format | Text |
id | pubmed-2447497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-24474972008-07-14 Using Multiple Ontologies to Integrate Complex Biological Data Shimoyama, Mary Petri, Victoria Pasko, Dean Bromberg, Susan Wu, Wenhua Chen, Jiali Nenasheva, Nataliya Kwitek, Anne Twigger, Simon Jacob, Howard Comp Funct Genomics Research Article The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease. Hindawi Publishing Corporation 2005 /pmc/articles/PMC2447497/ /pubmed/18629202 http://dx.doi.org/10.1002/cfg.498 Text en Copyright © 2005 Hindawi Publishing Corporation. http://creativecommons.org/licenses/by/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Shimoyama, Mary Petri, Victoria Pasko, Dean Bromberg, Susan Wu, Wenhua Chen, Jiali Nenasheva, Nataliya Kwitek, Anne Twigger, Simon Jacob, Howard Using Multiple Ontologies to Integrate Complex Biological Data |
title | Using Multiple Ontologies to Integrate Complex Biological Data |
title_full | Using Multiple Ontologies to Integrate Complex Biological Data |
title_fullStr | Using Multiple Ontologies to Integrate Complex Biological Data |
title_full_unstemmed | Using Multiple Ontologies to Integrate Complex Biological Data |
title_short | Using Multiple Ontologies to Integrate Complex Biological Data |
title_sort | using multiple ontologies to integrate complex biological data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447497/ https://www.ncbi.nlm.nih.gov/pubmed/18629202 http://dx.doi.org/10.1002/cfg.498 |
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