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BioEMR: an integrative framework for cancer research with multiple genomic technologies
The rapid development of omic technologies facilitate cancer researchers to apply multiple genomic technologies simultaneously. In fact, the complex nature of cancer biology is the reason why we need tools for data integration. Given the complexity of managing multiple technologies and dataset forma...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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American Medical Informatics Association
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041523/ https://www.ncbi.nlm.nih.gov/pubmed/21347128 |
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author | Park, Yu Rang Bae, Yun Jung Kim, Ju Han |
author_facet | Park, Yu Rang Bae, Yun Jung Kim, Ju Han |
author_sort | Park, Yu Rang |
collection | PubMed |
description | The rapid development of omic technologies facilitate cancer researchers to apply multiple genomic technologies simultaneously. In fact, the complex nature of cancer biology is the reason why we need tools for data integration. Given the complexity of managing multiple technologies and dataset formats, several projects have been introduced including cancer Biomedical Informatics Grid (caGRID) and the Biomedical Research Institute Domain Group (BRIDG) with limited applicability. We introduce an object-oriented data model, Cancer Genomics Object Model (CaGe-OM) for multiple genomics data and Xperanto-CaGe, a web-based application using CaGe-OM with hybrid object-relational mapping technique. The hybrid approach uses objectrelational mapping which is extended to include dynamic structure by using Entity-Attribute-Value (EAV) model. CaGe-OM and Xperanto-CaGe are an attempt to establish a comprehensive framework for integrated storage and interpretation of clinical and multiple genomics data and to facilitate model-level integration of other newly emerging data types. A pilot implementation for the integrated clinical, histo-pathological and genomic information systems is introduced. |
format | Text |
id | pubmed-3041523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-30415232011-02-23 BioEMR: an integrative framework for cancer research with multiple genomic technologies Park, Yu Rang Bae, Yun Jung Kim, Ju Han Summit on Translat Bioinforma Articles The rapid development of omic technologies facilitate cancer researchers to apply multiple genomic technologies simultaneously. In fact, the complex nature of cancer biology is the reason why we need tools for data integration. Given the complexity of managing multiple technologies and dataset formats, several projects have been introduced including cancer Biomedical Informatics Grid (caGRID) and the Biomedical Research Institute Domain Group (BRIDG) with limited applicability. We introduce an object-oriented data model, Cancer Genomics Object Model (CaGe-OM) for multiple genomics data and Xperanto-CaGe, a web-based application using CaGe-OM with hybrid object-relational mapping technique. The hybrid approach uses objectrelational mapping which is extended to include dynamic structure by using Entity-Attribute-Value (EAV) model. CaGe-OM and Xperanto-CaGe are an attempt to establish a comprehensive framework for integrated storage and interpretation of clinical and multiple genomics data and to facilitate model-level integration of other newly emerging data types. A pilot implementation for the integrated clinical, histo-pathological and genomic information systems is introduced. American Medical Informatics Association 2008-03-01 /pmc/articles/PMC3041523/ /pubmed/21347128 Text en ©2008 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose |
spellingShingle | Articles Park, Yu Rang Bae, Yun Jung Kim, Ju Han BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title | BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title_full | BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title_fullStr | BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title_full_unstemmed | BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title_short | BioEMR: an integrative framework for cancer research with multiple genomic technologies |
title_sort | bioemr: an integrative framework for cancer research with multiple genomic technologies |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041523/ https://www.ncbi.nlm.nih.gov/pubmed/21347128 |
work_keys_str_mv | AT parkyurang bioemranintegrativeframeworkforcancerresearchwithmultiplegenomictechnologies AT baeyunjung bioemranintegrativeframeworkforcancerresearchwithmultiplegenomictechnologies AT kimjuhan bioemranintegrativeframeworkforcancerresearchwithmultiplegenomictechnologies |