• Genomics & Informatics
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• 제11권1호
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• pp.38-45
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• 2013

In cancer genome studies, the annotation of newly detected oncogene/tumor suppressor gene candidates is a challenging process. We propose using concept lattice analysis for the annotation and interpretation of genes having candidate somatic mutations in whole-exome sequencing in acute myeloid leukemia (AML). We selected 45 highly mutated genes with whole-exome sequencing in 10 normal matched samples of the AML-M2 subtype. To evaluate these genes, we performed concept lattice analysis and annotated these genes with existing knowledge databases.

• Genomics & Informatics
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• 제15권1호
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• pp.51-53
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• 2017

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

• 유전체소식지
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• 제5권4호
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• pp.9-16
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• 2005

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic expression data transforms the challenges m biomedical research into ones in bioinformatics. Clinical informatics has long developed technologies to imp개ve biomedical research by integrating experimental and clinical information systems. Biomedical informatics, powered by high throughput techniques, genomic-scale databases and advanced clinical information system, is likely to transform our biomedical understanding forever much the same way that biochemistry did to biology a generation ago. The emergence of healthcare and biomedical informatics revolutionizing both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics and prognostics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1830-1840
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• 2011

CDISC (Clinical Data Interchanging Standards Consortium) standards are to support the acquisition, exchange, submission and archival of clinical trial and research data. SDTM (Study Data Tabulation Model) for Case Report Forms (CRFs) was recommended for U.S. Food and Drug Administration (FDA) regulatory submissions since 2004. Although the SDTM Implementation Guide gives a standardized and predefined collection of submission metadata 'domains' containing extensive variable collections, transforming CRFs to SDTM files for FDA submission is still a very hard and time-consuming task. For addressing this issue, we developed metadata based SDTM mapping rules. Using these mapping rules, we also developed a semi-automatic tool, named CDISC Transformer, for transforming clinical trial data to CDISC standard compliant data. The performance of CDISC Transformer with or without MDR support was evaluated using CDISC blank CRF as the 'gold standard'. Both MDR and user inquiry-supported transformation substantially improved the accuracy of our transformation rules. CDISC Transformer will greatly reduce the workloads and enhance standardized data entry and integration for clinical trial and research in various healthcare domains.

• Genomics & Informatics
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• 제3권1호
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• pp.39-42
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• 2005

DNA microarray is a high-throughput biomedical technology that monitors gene expression for thousands of genes in parallel. The abundance and complexity of the gene expression data have given rise to a requirement for their systematic management and analysis to support many laboratories performing microarray research. On these demands, we developed Xperanto for integrated data management and analysis using user-friendly web-based interface. Xperanto provides an integrated environment for management and analysis by linking the computational tools and rich sources of biological annotation. With the growing needs of data sharing, it is designed to be compliant to MGED (Microarray Gene Expression Data) standards for microarray data annotation and exchange. Xperanto enables a fast and efficient management of vast amounts of data, and serves as a communication channel among multiple researchers within an emerging interdisciplinary field.

• 대한위암학회:학술대회논문집
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• 대한위암학회 2005년도 제19회 춘계학술대회
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• pp.15-15
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• 2005

• Genomics & Informatics
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• 제3권3호
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• pp.68-73
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• 2005

Pharmacogenomics research requires an intelligent integration of large-scale genomic and clinical data with public and private knowledge resources. We developed a web-based knowledge base for KPRN (Korea Pharmacogenomics Research Network, http://kprn.snubi. org/). Four major types of information is integrated; genetic variation, drug information, disease information, and literature annotation. Eighteen Korean pharmacogenomics research groups in collaboration have submitted 859 genotype data sets for 91 disease-related genes. Integrative analysis and visualization of the large collection of data supported by integrated biomedical path­ways and ontology resources are provided with a user-friendly interface and visualization engine empowered by Generic Genome Browser.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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• pp.1-9
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• 2001

scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences and information technology. The informatics revolutions both in clinical informatics and bioinformatics will change the current paradigm of biomedical sciences and practice of clinical medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. In this talk, 1 will describe how these technologies will in pact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine teaming algorithms will be presented. Issues of integrated biochip informatics technologies including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples from ongoing research activities in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

• Genomics & Informatics
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• 제4권3호
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• pp.129-132
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• 2006

Toxicogenomics has recently emerged in the field of toxicology and the DNA microarray technique has become common strategy for predictive toxicology which studies molecular mechanism caused by exposure of chemical or environmental stress. Although microarray experiment offers extensive genomic information to the researchers, yet high dimensional characteristic of the data often makes it hard to extract meaningful result. Therefore we developed toxicant enrichment analysis similar to the common enrichment approach. We also developed web-based system graPT to enable considerable prediction of toxic endpoints of experimental chemical.

• Journal of Preventive Medicine and Public Health
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• 제35권2호
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• pp.83-91
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• 2002

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolutions both in bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. The paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization, primary pattern analysis, and machine learning algorithms will be presented. Use of integrated biochip informatics technologies, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.