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BioEMR: an integrative framework for cancer research with multiple genomic technologies
Yu Rang Park1, Yun Jung Bae, Ju Han Kim
1Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine;
Abstract:
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.
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