• Interdisciplinary Bio Central
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• 제3권2호
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• pp.7.1-7.6
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• 2011

Background: Published manuscripts are the main source of biological knowledge. Since the manual examination is almost impossible due to the huge volume of literature data (approximately 19 million abstracts in PubMed), intelligent text mining systems are of great utility for knowledge discovery. However, most of current text mining tools have limited applicability because of i) providing abstract-based search rather than sentence-based search, ii) improper use or lack of ontology terms, iii) the design to be used for specific subjects, or iv) slow response time that hampers web services and real time applications. Results: We introduce an advanced text mining system called PubMine that supports intelligent knowledge discovery based on diverse bio-ontologies. PubMine improves query accuracy and flexibility with advanced search capabilities of fuzzy search, wildcard search, proximity search, range search, and the Boolean combinations. Furthermore, PubMine allows users to extract multi-dimensional relationships between genes, diseases, and chemical compounds by using OLAP (On-Line Analytical Processing) techniques. The HUGO gene symbols and the MeSH ontology for diseases, chemical compounds, and anatomy have been included in the current version of PubMine, which is freely available at http://pubmine.kobic.re.kr. Conclusions: PubMine is a unique bio-text mining system that provides flexible searches and analysis of biological entity relationships. We believe that PubMine would serve as a key bioinformatics utility due to its rapid response to enable web services for community and to the flexibility to accommodate general ontology.

• 정보관리연구
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• 제40권1호
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• pp.157-181
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• 2009

전 세계적으로 정보기술이 발달하고 인간유전체사업이 종료됨에 따라 대용량 생명과학과 정보기술이 접목된 생명정보학(Bioinformatics, 바이오인포매틱스)이 등장하여 지속적으로 발전하고 있다. 이러한 학문의 발전과 더불어 생명정보서비스를 위한 웹사이트가 구축되어 생명과학 연구자들에게 제공되고 있다. 전 세계의 수많은 생명정보서비스 웹사이트 중에서 연구자들이 가장 많이 활용하는 대표적인 웹사이트로는 우리나라의 포항공과대학교 생물학연구전문정보센터(BRIC), 한국과학기술정보연구원 바이오인포매틱스센터(CCBB), 한국생명공학연구원 국가생물자원정보관리센터(KOBIC), 미국의 국립생명공학정보센터(NCBI), 유럽의 생물정보학연구소(EBI), 일본의 DNA데이터은행(DDBJ) 등이 있다. 본 논문에서는 위의 6개 웹사이트의 콘텐트 현황 및 기능을 조사하여 비교.분석하였다. 또한 웹사이트를 이용하는 생명과학 연구자를 대상으로 이용현황 및 요구사항에 관하여 설문조사를 실시하였다.

• 한국환경복원기술학회지
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• 제23권4호
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• pp.59-67
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• 2020

In this study, the effects of windbreak fences composed of natural vegetation on one-year-old seedlings were analyzed to develop restoration methods for an endangered subalpine species, the dwarf Siberian pine (Pinus pumila (Pall.) Regel). One-year-old seedlings were planted in 2016 by sowing seeds that had been collected from the Daecheongbong area on Mt. Seoraksan, South Korea, in 2014. The area near Daecheongbong was selected as the experimental site, and treatment and control plots (2m×2m) were installed at the site. To analyze the effects of wind protection, windbreak fences were constructed in the treatment plots using hairy Korean rhododendrons (Rhododendron mucronulatum Turcz. var. ciliatum Nakai) from the surrounding area and weather stations were installed to investigate atmospheric temperature, humidity, and wind speed. In all control plots without windbreak fences, dwarf Siberian pine seedlings were killed by strong winds seven months after planting. In contrast, the average survival rate of the seedlings in treatment plots was 96.7% after seven months, 64.2% after two years, and 45% after three years, with most (85.3%) of the seedlings showing good initial root establishment. Accordingly, windbreak fences composed of natural vegetation are suitable for promoting the early establishment of seedlings in the restoration of dwarf Siberian pine stands.

• Genomics & Informatics
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• 제5권4호
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• pp.196-199
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• 2007

BOD is an FTP service management tool on the Internet. It was developed for biological researchers in South Korea. It enables easier and faster access of bioinformation without having to go through foreign FTP sites. BOD includes an automatic downloader with a management and email alert service from which the user can easily select and schedule any biological database. Once listed in BOD, the user can check and modify the download status and data from an additional email alert service.

• Genomics & Informatics
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• 제18권1호
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• pp.8.1-8.10
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• 2020

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.

• Journal of Microbiology and Biotechnology
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• 제16권2호
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• pp.178-183
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• 2006

Microbes are one of the most important bioresources in bioindustry and provide high economic values. Although there are currently about 6,000 bacterial species with validly published names, microbiologists generally assume that the number may account for less than 1% of the bacterial species present on Earth. To discover the remaining species, studies of metagenomes, metabolomes, and proteomes related to microbes have recently been carried out in various fields. We have constructed an information system that integrates various data on microbial resources and manages bioinformation to support efficient research of microorganisms. We have designated this system 'Bio-Meta Information System (Bio-MIS).' Bio-MIS consists of an integrated microbial resource database, a microbial resource input system, an integrated microbial resource search engine, a microbial resource online distribution system, a portal service, and management via the Internet. In the future, this system is expected to be connected with various public databases. We plan to implement useful bioinformatics software for analyzing microbial genome resources. The Web site is accessible at http://biomis.probionic.com.