• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.123-123
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• 2003

• Journal of Life Science
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• v.12 no.4
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• pp.383-391
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• 2002

The difficulties in dealing with the Bioinformatics data come more from its idiosyncrasies than from its quantity Currently researchers need to an easy method for data exchange, manage, update. In order to integrate and manage all kinds of biological data, it is reasonable to adopt XML as standard tool since XML is independent of operating system, programming language and hardware platform. Although XML in Bioinformatics has been used widely as a standard notation abroad, however it is the beginning step in the domestic research. This article reviews a basic concept of XML and how to apply XML modeling in Bioinformatics. In addition we present XML applications for genomic sequences, structures and genetic network modeling.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.770-773
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• 2005

In most biological laboratory, sequences from sequence machine are stored into file disks as simple files. It will be hard work to store and manage the sequence data with consistency and integrity such as storing redundant files. It is required needed to develop a system which integrated and managed genome data with consistency and integrity for accurate sequence analysis. There fore, in this paper, we not only store gene and protein sequence data through sequencing but also manage them. We also make a integrate schema for transforming the file formats and design database system using it. As integrated schema is designed as a BSML, it is possible to apply a style language of XSL. From this, we can transfer among heterogeneous sequence formats.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.236-244
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• 2003

Summary: The analysis of human genetic variation is one of the key issues far the understanding of the different drug response among individuals and many programs are developed for this purpose. However, current publicly available programs have so many limitations such as time complexity problem for the analysis of large amount of alleles or SNPs, difficult manipulation for installation, data import, and usage, and low-quality visual output. Here we present workbench for SNP anlaysis, SNPAnalyzer. SNPAnalyzer consists of 3 main modules: 1)Hardy-Weinberg Equilibrium ,2) Haplotype Estimation, and 3) Linkage Disequilibrium. Each module has several different widely-used algorithms for the extensive analysis and can handle large amount of alleles and SNPs with simple format. Analysis results are displayed in user-friendly formats such as table, graph and map. SNPAnalyzer is developed using C and C$^{++}$ and users can easily access through web-interftce. Availability: SNPAnalyzer can be freely implemented at http://www.istech.info/istech/board/login_form.jsp

• Genomics & Informatics
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• v.11 no.1
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• pp.52-54
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• 2013

Proteins in DNAJ/K families are ubiquitous, from prokaryotes to eukaryotes, and function as molecular chaperones. For systematic phylogenomics of the DNAJ/K families, we developed the Eukaryotic DNAJ/K Database (EDD). A total of 12,908 DNAJs and 4,886 DNAKs were identified from 339 eukaryotic genomes in the EDD. Kingdom-wide comparison of DNAJ/K families provides new insights on the evolutionary relationship within these families. Empowered by 'class', 'cluster', and 'taxonomy' browsers and the 'favorite' function, the EDD provides a versatile platform for comparative genomic analyses of DNAJ/K families.

• Journal of Genetic Medicine
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• v.10 no.1
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• pp.27-32
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• 2013

Post-transcriptional nucleotide sequence modification of transcripts by RNA editing is an important molecular mechanism in the regulation of protein function and is associated with a variety of human disease phenotypes. Identification of RNA editing sites is the basic step for studying RNA editing. Databases and bioinformatics resources are used to annotate and evaluate as well as identify RNA editing sites. No method is free of limitations. Correctly establishing an analytic pipeline and strategic application of both experimental and bioinformatics methods constitute the first step in investigating RNA editing. This review summarizes modern bioinformatics approaches and related resources for RNA editing research.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.833-836
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• 2003

본 논문에서는 생물학적 문헌으로부터 유의미한 정보를 추출하는 바이오 텍스트 마이닝의 기본 단계인 생물학적 개체명 인식 모델을 제안하였다. 기존의 생물학적 개체명 인식은 규칙 혹은 코퍼스 구축뿐만 아니라 개체명 인식에 요구되는 기본 자원을 구축하는데만도 많은 시간과 비용이 요구되므로 한정된 도메인을 대상으로 연구가 진행되어 왔다. 본 논문에서 제안하는 개체명 인식 방법은 이러한 비용 문제 및 새로운 도메인으로의 이식성 문제를 극복하기 위해 UMLS 로부터 통계적인 방법으로 정보를 추출해 기본적인 언어자원을 구축하고 이를 이용해 규칙을 생성함으로써 개체명인식을 수행한다. 본 연구에서 제안하는 방법은 바이오 텍스트 마이닝 연구의 도메인 한정적인 문제를 해결하는데 기여할 수 있을 것으로 기대된다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.289-291
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• 2005

최근 유전자 칩의 발전으로 다양하고 방대한 양의 유전자 정보를 이용한 정확하고 신뢰성 높은 분류, 군집 및 질병을 예측하는 분석 기법이 증가하고 있다. 하지만 특징적인 유전자를 선택하는 Gene Selection 기법의 종류는 많지가 않으며 주로 통계적인 방법에 의존하여 유전자를 선택하는 기법을 많이 사용하고 있다. 본 논문에서는 유전자 알고리즘과 신경망의 결합을 통한 데이터마이닝을 기반으로 신뢰성 높은 특징적인 유전자를 선택하는 Gene Selection 기법에 대하여 연구을 진행하였다.

• Genomics & Informatics
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• v.16 no.3
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• pp.75-77
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• 2018

Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Text corpus for this journal annotated with various levels of linguistic information would be a valuable resource as the process of information extraction requires syntactic, semantic, and higher levels of natural language processing. In this study, we publish our new corpus called GNI Corpus version 1.0, extracted and annotated from full texts of Genomics & Informatics, with NLTK (Natural Language ToolKit)-based text mining script. The preliminary version of the corpus could be used as a training and testing set of a system that serves a variety of functions for future biomedical text mining.