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Biomedical subjects

Yu Rang Park

Publications and source records attributed to Yu Rang Park.

3 recordsLinked to original sources

The tissue microarray object model: a data model for storage, analysis, and exchange of tissue microarray experimental data.

CONTEXT: Tissue microarray (TMA) is an array-based technology allowing the examination of hundreds of tissue samples on a single slide. To handle, exchange, and disseminate TMA data, we need standard representations of the methods used, of the data generated, and of the clinical and histopathologic information related to TMA data analysis. OBJECTIVE: To create a comprehensive data model with flexibility that supports diverse experimental designs and with expressivity and extensibility that enables an adequate and comprehensive description of new clinical and histopathologic data elements. DESIGN: We designed a tissue microarray object model (TMA-OM). Both the array information and the experimental procedure models are created by referring to the microarray gene expression object model, minimum information specification for in situ hybridization and immunohistochemistry experiments, and the TMA data exchange specifications. The clinical and histopathologic information model is created by using College of American Pathologists cancer protocols and National Cancer Institute common data elements. Microarray Gene Expression Data Ontology, the Unified Medical Language System, and the terms extracted from College of American Pathologists cancer protocols and NCI common data elements are used to create a controlled vocabulary for unambiguous annotation. RESULT: The TMA-OM consists of 111 classes in 17 packages to represent clinical and histopathologic information as well as experimental data for any type of cancer. We implemented a Web-based application for TMA-OM, supporting data export in XML format conforming to the TMA data exchange specifications or the document type definition derived from TMA-OM. CONCLUSIONS: The TMA-OM provides a comprehensive data model for storage, analysis, and exchange of TMA data and facilitates model-level integration of other biological models.

Gene Expression Profiling↗

Integrating microarray gene expression object model and clinical document architecture for cancer genomics research.

Systematic integration of genomic-scale expression profiles with clinical information may facilitate cancer genomics research. MAGE-OM (Microarray Gene Expression Object Model) defines standard objects for genomic but not for clinical data. HL7 CDA (Clinical Document Architecture) is a document model for clinical information, describing syntax (generic structure) but not semantics. We designed a document template in XML Schema with additional constraints for CDA to define content semantics, enabling data model-level integration of MAGE-OM and CDA for cancer genomics research.

Gene Expression Profiling↗

GOChase: correcting errors from Gene Ontology-based annotations for gene products.

SUMMARY: The Gene Ontology (GO) is a controlled biological vocabulary that provides three structured networks of terms to describe biological processes, cellular components and molecular functions. Many databases of gene products are annotated using the GO vocabularies. We found that some GO-updating operations are not easily traceable by the current biological databases and GO browsers. Consequently, numerous annotation errors arise and are propagated throughout biological databases and GO-based high-level analyses. GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.

Database Management Systems↗