• Genomics & Informatics
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• v.3 no.2
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• pp.47-51
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• 2005

Molecular mechanisms of biological processes are typically represented as 'pathways' that have a graph­analogical network structure. However, due to the diversity of topics that pathways cover, their constituent biological entities are highly diverse and the semantics is embedded implicitly. The kinds of interactions that connect biological entities are likewise diverse. Consequently, how to model or process pathway data is not a trivial issue. In this review article, we give an overview of the challenges in pathway database development by taking the INOH project as an example.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.383-387
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• 2005

One of the most important issues in post-genome era is identifying functions of genes and understanding the interaction among them. Such interactions from complex biochemical pathways, which are very useful to understand the organism system. We present an integrated biochemical pathway database system with a set of software tools for reconstruction, visualization, and simulation of the pathways from the database. The novel features of the presented system include: (a) automatic integration of the heterogeneous biochemical pathway databases, (b) gene ontology for high quality of database in the integration and query (c) various biochemical simulations on the pathway database, (d) dynamic pathway reconstruction for the gene list or sequence data, (e) graphical tools which enable users to view the reconstructed pathways in a dynamic form, (f) importing/exporting SBML documents, a data exchange standard for systems biology.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.76-91
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• 2020

Whole genome sequence of Abeliophyllum distichum Nakai (Oleaceae) cultivar Ok Hwang 1 Ho, which is Korean endemic species, was recently sequenced to understand its characteristics. Acteoside is one of major useful compounds presenting various activities, and its several proposed biochemical pathways were reviewed and integrated to make precise biochemical pathway. Utilizing MetaPre-AI^TM which was developed for predicting secondary metabolites based on whole genome with the precise biochemical pathway of acteoside and the InfoBoss Pathway Database, we successfully rescued all enzymes involved in this pathway from the genome sequences, presenting that A. distichum cultivar Ok Hwang 1 Ho may produce acteoside. High-performance liquid chromatography result displayed that callus of A. distichum cultivar Ok Hwang 1 Ho contained acteoside as well as isoacteoside which may be derived from acteoside. Taken together, we successfully showed that MetaPre-AI^TM can predict secondary metabolite from plant whole genomes. In addition, this method will be efficient to predict secondary metabolites of many plant species because DNA can be analyzed more stability than chemical compounds.

• Genomics & Informatics
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• v.7 no.1
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• pp.38-40
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• 2009

The EST Knowledge Integrated System, EKIS (http://ekis.kribb.re.kr), was established as a part of Korea's Ministry of Education, Science and Technology initiative for genome sequencing and application research of the biological model organisms (GEAR) project. The goals of the EKIS are to collect EST information from GEAR projects and make an integrated database to provide transcriptomic and metabolomic information for biological scientists. The EKIS constitutes five independent categories and several retrieval systems in each category for incorporating massive EST data from high-throughput sequencing of 65 different species. Through the EKIS database, scientists can freely access information including BLAST functional annotation as well as Genechip and pathway information for KEGG. By integrating complex data into a framework of existing EST knowledge information, the EKIS provides new insights into specialized metabolic pathway information for an applied industrial material.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.56-58
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• 2000

Post-genomics may be defined in different ways depending on how one views the challenges after the genome. A popular view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are going on to analyze gene expression profiles both at the mRNA and protein levels and to catalog protein 3D structure families, which will no doubt help the understanding of information in the genome. However complete, such catalogs of genes, RNAs, and proteins only tell us about the building blocks of life. They do not tell us much about the wiring (interaction) of building blocks, which is essential for uncovering systemic functional behaviors of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level, and to understand, what I call, the "interactome"or a complete picture of molecular interactions in the cell. KEGG (http://www.genome.ad.jp/kegg/) is our attempt to computerize current knowledge on various cellular processes as a collection of "generalized"protein-protein interaction networks, to develop new graph-based algorithms for predicting such networks from the genome information, and to actually reconstruct the interactomes for all the completely sequenced genomes and some partial genomes. During the reconstruction process, it becomes readily apparent that certain pathways and molecular complexes are present or absent in each organism, indicating modular structures of the interactome. In addition, the reconstruction uncovers missing components in an otherwise complete pathway or complex, which may result from misannotation of the genome or misrepresentation of the KEGG pathway. When combined with additional experimental data on protein-protein interactions, such as by yeast two-hybrid systems, the reconstruction possibly uncovers unknown partners for a particular pathway or complex. Thus, the reconstruction is tightly coupled with the annotation of individual genes, which is maintained in the GENES database in KEGG. We are also trying to expand our literature surrey to include in the GENES database most up-to-date information about gene functions.

• Molecular & Cellular Toxicology
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• v.3 no.3
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• pp.208-213
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• 2007

With the help of a development and popularization of microarray technology that enable to us to simultaneously investigate the expression pattern of thousands of genes, the toxicogenomics experimenters can interpret the genome-scale interaction between genes exposed in toxicant or toxicant-related environment. The ultimate and primary goal of toxicogenomics identifies functional context among the group of genes that are differentially or similarly coexpressed under the specific toxic substance. On the other side, public reference databases with transcriptom, proteom, and biological pathway information are needed for the analysis of these complex omics data. However, due to the heterogeneous and independent nature of these databases, it is hard to individually analyze a large omics annotations and their pathway information. Fortunately, several web sites of the public database provide information linked to other. Nevertheless it involves not only approriate information but also unnecessary information to users. Therefore, the systematically integrated database that is suitable to a demand of experimenters is needed. For these reasons, we propose SOP (Search of Omics Pathway) database system which is constructed as the integrated biological database converting heterogeneous feature of public databases into combined feature. In addition, SOP offers user-friendly web interfaces which enable users to submit gene queries for biological interpretation of gene lists derived from omics experiments. Outputs of SOP web interface are supported as the omics annotation table and the visualized pathway maps of KEGG PATHWAY database. We believe that SOP will appear as a helpful tool to perform biological interpretation of genes or proteins traced to omics experiments, lead to new discoveries from their pathway analysis, and design new hypothesis for a next toxicogenomics experiments.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.407-411
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• 2005

KUGI (Korean UniGene Information) database contains the annotation information of the cDNA sequences obtained from the disease samples prevalent in Korean. A total of about 157,000 5'-EST high throughput sequences collected from cDNA libraries of stomach, liver, and some cancer tissues or established cell lines from Korean patients were clustered to about 35,000 contigs. From each cluster a representative clone having the longest high quality sequence or the start codon was selected. We stored the sequences of the representative clones and the clustered contigs in the KUGI database together with their information analyzed by running Blast against RefSeq, human mRNA, and UniGene databases from NCBI. We provide a web-based search engine fur the KUGI database using two types of user interfaces: attribute-based search and similarity search of the sequences. For attribute-based search, we use DBMS technology while we use BLAST that supports various similarity search options. The search system allows not only multiple queries, but also various query types. The results are as follows: 1) information of clones and libraries, 2) accession keys, location on genome, gene ontology, and pathways to public databases, 3) links to external programs, and 4) sequence information of contig and 5'-end of clones. We believe that the KUGI database and search system may provide very useful information that can be used in the study for elucidating the causes of the disease that are prevalent in Korean.

• Korean Journal of Poultry Science
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• v.37 no.3
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• pp.275-282
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• 2010

Chicken is an important livestock as a valuable biomedical model as well as food for human, and there is a strong rationale for improving our understanding on metabolism and physiology of this organism. The first draft of chicken genome assembly was released in 2004, which enables elaboration on the linkage between genetic and metabolic traits of chicken. The objectives of this study were thus to reconstruct metabolic pathway of the chicken genome and to construct a chicken specific pathway genome database (PGDB). We developed a comprehensive genome database for chicken by integrating all the known annotations for chicken genes and proteins using a pipeline written in Perl. Based on the comprehensive genome annotations, metabolic pathways of the chicken genome were reconstructed using the PathoLogic algorithm in Pathway Tools software. We identified a total of 212 metabolic pathways, 2,709 enzymes, 71 transporters, 1,698 enzymatic reactions, 8 transport reactions, and 1,360 compounds in the current chicken genome build, Gallus_gallus-2.1. Comparative metabolic analysis with the human, mouse and cattle genomes revealed that core metabolic pathways are highly conserved in the chicken genome. It was indicated the quality of assembly and annotations of the chicken genome need to be improved and more researches are required for improving our understanding on function of genes and metabolic pathways of avian species. We conclude that the chicken PGDB is useful for studies on avian and chicken metabolism and provides a platform for comparative genomic and metabolic analysis of animal biology and biomedicine.

• Genomics & Informatics
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• v.4 no.4
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• pp.182-187
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• 2006

6-Phosphogluconolactonase (6PGL) is one of the key enzymes in the ubiquitous pathways of central carbon metabolism, but bacterial 6PGL had been long known as a missing enzyme even after complete bacterial genome sequence information became available. Although recent experimental characterization suggests that there are two types of 6PGLs (DevB and YbhE), their phylogenetic distribution is severely biased. Here we present that proteins in COG group previously described as 3-oarboxymuconate cyclase (COG2706) are actually the YbhE-type 6PGLs, which are widely distributed in Proteobacteria and Fimicutes. This case exemplifies how erroneous functional description of a member in the reference database commonly used in transitive genome annotation cause systematic problem in the prediction of genes even with universal cellular functions.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.290-296
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• 2019

Objective: Pigs share many physiological, anatomical and genomic similarities with humans, which make them suitable models for biomedical researches. Understanding the genetic status of Yucatan miniature pigs (YMPs) and their association with human diseases will help to assess their potential as biomedical model animals. This study was performed to identify non-synonymous single nucleotide polymorphisms (nsSNPs) in selective sweep regions of the genome of YMPs and present the genetic nsSNP distributions that are potentially associated with disease occurrence in humans. Methods: nsSNPs in whole genome resequencing data from 12 YMPs were identified and annotated to predict their possible effects on protein function. Sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 analyses were used, and gene ontology (GO) network and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Results: The results showed that 8,462 genes, encompassing 72,067 nsSNPs were identified, and 118 nsSNPs in 46 genes were predicted as deleterious. GO network analysis classified 13 genes into 5 GO terms (p<0.05) that were associated with kidney development and metabolic processes. Seven genes encompassing nsSNPs were classified into the term associated with Alzheimer's disease by referencing the genetic association database. The KEGG pathway analysis identified only one significantly enriched pathway (p<0.05), hsa04080: Neuroactive ligand-receptor interaction, among the transcripts. Conclusion: The number of deleterious nsSNPs in YMPs was identified and then these variants-containing genes in YMPs data were adopted as the putative human diseases-related genes. The results revealed that many genes encompassing nsSNPs in YMPs were related to the various human genes which are potentially associated with kidney development and metabolic processes as well as human disease occurrence.