• Genomics & Informatics
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• 제9권2호
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• pp.85-88
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• 2011

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a biological information-based database. The major functions of the NABIC are focused on biotechnological developments for agricultural bioinformatics and providing a web-based service to construct bioinformatics workflows easily, such as protein function prediction and genome systems biology programs. The NABIC has concentrated on the functional genomics of major crops, building an integrated biotechnology database for agro-biotech information that focuses on the proteomics of major agricultural resources, such as rice, Chinese cabbage, rice Ds-tagging lines, and microorganisms.

• Mycobiology
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• 제35권3호
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• pp.154-156
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• 2007

A database application, namely MushBase, has been built based on Microsoft Access in order to store and manage different kinds of data about mushroom biological information of species, strains and their physiological characteristics such as geometries and growth condition(s). In addition, it is also designed to store another group of information that is experimental data about mushroom classification by Random Amplification of Polymorphic DNA (RAPD). These two groups of information are stored and managed in the way so that it is convenient to retrieve each group of data and to cross-refer between them as well.

• Genomics & Informatics
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• 제6권4호
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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.

• Journal of Microbiology and Biotechnology
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• 제24권10호
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• pp.1301-1307
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• 2014

White-rot fungi of the genus Bjerkandera are cosmopolitan and have shown potential for industrial application and bioremediation. When distinguishing morphological characters are no longer present (e.g., cultures or dried specimen fragments), characterizing true sequences of Bjerkandera is crucial for accurate identification and application of the species. To build a framework for molecular identification of Bjerkandera, we carefully identified specimens of B. adusta and B. fumosa from Korea based on morphological characters, followed by sequencing the internal transcribed spacer region and 28S nuclear ribosomal large subunit. The phylogenetic analysis of Korean Bjerkandera specimens showed clear genetic differentiation between the two species. Using this phylogeny as a framework, we examined the identification accuracy of sequences available in GenBank. Analyses revealed that many Bjerkandera sequences in the database are either misidentified or unidentified. This study provides robust reference sequences for sequence-based identification of Bjerkandera, and further demonstrates the presence and dangers of incorrect sequences in GenBank.

• Molecules and Cells
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• 제21권2호
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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

• Parasites, Hosts and Diseases
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• 제47권2호
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• pp.103-107
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• 2009

The genus Acanthamoeba can cause severe infections such as granulomatous amebic encephalitis and amebic keratitis in humans. However, little genomic information of Acanthamoeba has been reported. Here, we constructed Acanthamoeba expressed sequence tags (EST) database (Acanthamoeba EST DB) derived from our 4 kinds of Acanthamoeba cDNA library. The Acanthamoeba EST DB contains 3,897 EST generated from amebae under various conditions of long term in vitro culture, mouse brain passage, or encystation, and downloaded data of Acanthamoeba from National Center for Biotechnology Information (NCBI) and Taxonomically Broad EST Database (TBestDB). The almost reported eDNA/genomic sequences of Acanthamoeba provide stand alone BLAST system with nucleotide (BLAST NT) and amino acid (BLAST AA) sequence database. In BLAST results, each gene links for the significant information including sequence data, gene orthology annotations, relevant references, and a BlastX result. This is the first attempt for construction of Acanthamoeba database with genes expressed in diverse conditions. These data were integrated into a database (http://www. amoeba.or.kr).

• 식물분류학회지
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• 제37권3호
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• pp.309-321
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• 2007

산림청 국립수목원과 한국식물분류학회가 공동으로 국내 최초로 전산화된 식물목록 데이터베이스를 구축하였다. 그 결과로 재배종을 포함한 약 7,000 분류군을 대상으로 항상 최신의 자료를 갱신할 수 있는 국가표준식물목록을 온라인상에 구현하였다. 국가표준식물목록은 37명의 국내 전문분류학자가 참여한 우리나라 식물목록과 관련된 최대 규모의 프로젝트이다. 본 연구는 국가표준식물목록 생성과정을 분석하고 이를 통해 관계형 데이터베이스 모델을 수립하였다. 개발된 광릉 데이터베이스 모델은 식물목록과 관련된 문헌과 다양한 분류학 자료를 제공할 수 있도록 설계 되었다. 이 모델은 다양한 분류학적 수준의 학명과 잡종명, 재배명, 이명, 기본명, 국명 및 명명법과 관련된 기타 자료를 함께 제공할 수 있다. 따라서, 국가표준식물목록 데이터베이스는 앞으로 개발될 생물정보시스템들의 개발에 있어 식물의 학명과 관련된 정확하고 일관성이 있는 표준 데이터베이스 기반을 제공하게 되었다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2002년도 제1차워크샵
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.1-8
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• 2019

Coronaviruses are known respiratory pathogens. In the past, most human coronaviruses were thought to cause mild symptoms such as cold. However recently, as seen in the Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS), infectious diseases with severe pulmonary disease and respiratory symptoms are caused by coronaviruses, making research on coronaviruses become important. Considering previous studies, we constructed 'HCoV-IMDB (Human Corona Virus Immune Database)' to systematically provide genetic information on human coronavirus and host immune information, which can be used to analyze the interaction between human coronavirus and host immune proteins. The 'HCoV-IMDB' constructed in the study can be used to search for genetic information on human coronavirus and host immune protein and to download data. A BLAST search specific to the human coronavirus, one of the database functions, can be used to infer genetic information and evolutionary relationship about the query sequence.

• Genomics & Informatics
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• 제13권1호
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• pp.7-14
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• 2015

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and $Prot{\acute{e}}g{\acute{e}}$ as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.