• Molecules and Cells
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• v.21 no.2
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• pp.269-275
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• 2006

A recent report of the Korean Intellectual Property Office(KIPO) showed that the number of biological sequence-based patents is rapidly increasing in Korea. We present biological features of Korean patented sequences though bioinformatic analysis. The analysis is divided into two steps. The first is an annotation step in which the patented sequences were annotated with the Reference Sequence (RefSeq) database. The second is an association step in which the patented sequences were linked to genes, diseases, pathway, and biological functions. We used Entrez Gene, Online Mendelian Inheritance in Man (OMIM), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) databases. Through the association analysis, we found that nearly 2.6% of human genes were associated with Korean patenting, compared to 20% of human genes in the U.S. patent. The association between the biological functions and the patented sequences indicated that genes whose products act as hormones on defense responses in the extra-cellular environments were the most highly targeted for patenting. The analysis data are available at http://www.patome.net

• Journal of Life Science
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• v.29 no.1
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• pp.123-128
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• 2019

The use of 16S rDNA is commonplace in the determination of prokaryotic species. However, it has limitations, and there are few studies at the genus level. We investigated conserved genes and metabolic pathways at the genus level in 28 strains of 13 genera of prokaryotes using the COG database (conserved genes) and MetaCyc database (metabolic pathways). Conserved genes compared to total genes (core genome) at the genus level ranged from 27.62%(Nostoc genus) to 71.76%(Spiribacter genus), with an average of 46.72%. The lower ratio of core genome meant the higher ratio of peculiar genes of a prokaryote, namely specific biological activities or the habitat may be varied. The ratio of common metabolic pathways at the genus level was higher than the ratio of core genomes, from 58.79% (Clostridium genus) to 96.31%(Mycoplasma genus), with an average of 75.86%. When compared among other genera, members of the same genus were positioned in the closest nodes to each other. Interestingly, Bacillus and Clostridium genera were positioned in closer nodes than those of the other genera. Archaebacterial genera were grouped together in the ortholog and metabolic pathway nodes in a phylogenetic tree. The genera Granulicella, Nostoc, and Bradyrhizobium of the Acidobacteria, Cyanobacteria, and Proteobacteria phyla, respectively, were grouped in an ortholog content tree. The results of this study can be used for (i) the identification of common genes and metabolic pathways at each phylogenetic level and (ii) the improvement of strains through horizontal gene transfer or site-directed mutagenesis.

• Genomics & Informatics
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• v.3 no.3
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• pp.86-93
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• 2005

Human brain EST data provide important clues for our understanding of the molecular biology associated with the function of the normal brain and the molecular pathophysiology with brain disorders. To systematically and efficiently study the function and disorders of the human brain, 45,773 human brain ESTs were collected from 27 human brain cDNA libraries, which were constructed from normal brains and brain disorders such as brain tumors, Parkinson's disease (PO) and epilepsy. An analysis of 45,773 human brain ESTs using our EST analysis pipeline resulted in 38,396 high-quality ESTs and 35,906 ESTs, which were coalesced into 8,246 unique gene clusters, showing a significant similarity to known genes in the human RefSeq, human mRNAs and UniGene database. In addition, among 8,246 gene clusters, 4,287 genes ($52\%$) were found to contain full-length cONA clones. To facilitate the extraction of useful information in collected these human brain ESTs, we developed a user-friendly interface system, the Korea Brain Unigene Database (KBUD). The KBUD web interface allows access to our human brain data through three major search modes, the BioCarta pathway, keywords and BLAST searches. Each result when viewed in KBUD offers comprehensive information concerning the analyzed human brain ESTs provided by our data as well as data linked to various other publiC databases. The user-friendly developed KBUD, the first world-wide web interface for human brain EST data with ESTs of human brain disorders as well as normal brains, will be a helpful system for developing a better understanding of the underlying mechanisms of the normal brain well as brain disorders. The KBUD system is freely accessible at http://kugi.kribb.re.kr/KU/cgi -bin/brain. pI.

• Genomics & Informatics
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• v.7 no.3
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• pp.175-177
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• 2009

We have developed WinBioDBs with Windows interfaces, which include importing modules and searching interfaces for 10 major public databases such as GenBank, PIR, SwissProt, Pathway, EPD, ENZYME, REBASE, Prosite, Blocks, and Pfam. User databases can be constructed with searching results of queries and their entries can be edited. The program is a stand-alone database searching program on Windows PC. Database update features are supported by importing raw database files and indexing after downloading them. Users can adjust their own searching environments and report format and construct their own projects consisting of a combination of a local databases. WinBioDBs are implemented with VC++ and its database is based on MySQL.

• Genomics & Informatics
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• v.6 no.4
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• pp.202-209
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• 2008

Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.135-135
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• 2017

The Gramene database (http://www.gramene.org) is a powerful online resource for agricultural researchers, plant breeders and educators that provides easy access to reference data, visualizations and analytical tools for conducting cross-species comparisons. Learn the benefits of using Gramene to enrich your lectures, accelerate your research goals, and respond to your organismal community needs. Gramene's genomes portal hosts browsers for 44 complete reference genomes, including crops and model organisms, each displaying functional annotations, gene-trees with orthologous and paralogous gene classification, and whole-genome alignments. SNP and structural diversity data, available for 11 species, are displayed in the context of gene annotation, protein domains and functional consequences on transcript structure (e.g., missense variant). Browsers from multiple species can be viewed simultaneously with links to community-driven organismal databases. Thus, while hosting the underlying data for comparative studies, the portal also provides unified access to diverse plant community resources, and the ability for communities to upload and display private data sets in multiple standard formats. Our BioMart data mining interface enable complex queries and bulk download of sequence, annotation, homology and variation data. Gramene's pathway portal, the Plant Reactome, hosts over 240 pathways curated in rice and inferred in 66 additional plant species by orthology projection. Users may compare pathways across species, query and visualize curated expression data from EMBL-EBI's Expression Atlas in the context of pathways, analyze genome-scale expression data, and conduct pathway enrichment analysis. Our integrated search database and modern user interface leverage these diverse annotations to facilitate finding genes through selecting auto-suggested filters with interactive views of the results.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1795-1801
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• 2018

Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.

• Genomics & Informatics
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• v.16 no.4
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• pp.28.1-28.6
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• 2018

Due to the increasing interest in synonymous codons, several codon bias-related terms were introduced. As one measure of them, the tRNA adaptation index (tAI) was invented about a decade ago. The tAI is a measure of translational efficiency for a gene and is calculated based on the abundance of intracellular tRNA and the binding strength between a codon and a tRNA. The index has been widely used in various fields of molecular evolution, genetics, and pharmacology. Afterwards, an improved version of the index, named specific tRNA adaptation index (stAI), was developed by adapting tRNA copy numbers in species. Although a subsequently developed webserver (stAIcalc) provided tools that calculated stAI values, it was not available to access pre-calculated values. In addition to about 100 species in stAIcalc, we calculated stAI values for whole coding sequences in 148 species. To enable easy access to this index, we constructed a novel web database, named STADIUM (Species-specific tRNA adaptive index compendium). STADIUM provides not only the stAI value of each gene but also statistics based on pathway-based classification. The database is expected to help researchers who have interests in codon optimality and the role of synonymous codons. STADIUM is freely available at http://stadium.pmrc.re.kr.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.295-297
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• 2004

유전자의 생물학적 기능을 밝히고 세포 내 상호작용을 이해하는 것은 post-genome era의 가장 중요한 작업 중 하나이다. 이러한 세포 내 상호작용은 복잡한 생화학적 네트워크를 형성하게 되며 그 중 Metabolic pathway(대사 경로)는 생물 시스템을 이해하는데 가장 중요한 부분을 차지하게 된다. 대사 경로를 분석하기 위하여 분자의 기능 및 생화학적 프로세스에 대한 정보를 데이터베이스에 저장.관리해야하고, 사용자의 다양한 질의에 대하여 관련정보를 검색하여 GUI환경에서 제공해야 한다. 이 논문은 대사 경로 정보를 객체 데이타베이스 형태로 모델링하여 구축하고, 사용자가 관심있는 정보를 SBML형태로 제공하는 대사경로 데이타베이스의 설계 및 구현에 관해 다룬다.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.