• Title/Summary/Keyword: Bioinformation Service

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PubMine: An Ontology-Based Text Mining System for Deducing Relationships among Biological Entities

  • Kim, Tae-Kyung;Oh, Jeong-Su;Ko, Gun-Hwan;Cho, Wan-Sup;Hou, Bo-Kyeng;Lee, Sang-Hyuk
    • Interdisciplinary Bio Central
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    • v.3 no.2
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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.

A Comparative Analysis of Bioinformation Website Services (생명정보 분야 웹사이트 서비스에 대한 비교.분석에 관한 연구)

  • Ahn, Bu-Young;Lee, Eung-Bong
    • Journal of Information Management
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    • v.40 no.1
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    • pp.157-181
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    • 2009
  • As the information technology is evolved and the human genome project is finalized over the world, the Bioinformatics - the integration of abundant Biological science and information technology - has shown up and is continuously being advanced. Together with the evolution of Bioinformatics, the websites dealing with Bioinformation have been set up to provide relevant information to the Bioscientists. Among the numerous global websites, the preferred websites by the majority of domestic Bioscientists are BRIC (Biological Research Information Center) of POSTECH(Pohang University of Science and Technology) in Korea, CCBB(Center for Computational Biology and Bioinformatics) of KISTI(Korea Institute of Science and Technology Information), KOBIC(Korean Bioinformation Center) of KRIBB(Korea Research Institute of Bioscience and Biotechnology), NCBI(National Center for Biotechnology Information) in USA, EBI(European Bioinformatics Institute) in Europe and DDBJ(DNA Data Bank of Japan) in Japan. In this paper, the comparative analysis was executed by investigating contents status and functions of the above-mentioned 6 websites. In addition, questionnaire survey of Bioscience Researchers' utilization status and their needs to those 6 websites was conducted.

Effects of Windbreak Fences Composed of Natural Vegetation on Dwarf Siberian Pine (Pinus pumila) Seedlings (식생을 이용한 방풍책이 눈잣나무 유묘에 미치는 영향)

  • Lim, Hyo-In;Chae, Seung-Beom;Lee, Seon-Uk;Ku, Ja-Jung
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.23 no.4
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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.

Biological Object Downloader (BOD) Service for Easy Download and Management of Biological Databases

  • Park, Dae-Ui;Lee, Jung-Woo;Yoon, Gi-Seok;Gong, Sung-Sam;Bhak, Jong
    • Genomics & Informatics
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    • v.5 no.4
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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.

Bioinformatics services for analyzing massive genomic datasets

  • Ko, Gunhwan;Kim, Pan-Gyu;Cho, Youngbum;Jeong, Seongmun;Kim, Jae-Yoon;Kim, Kyoung Hyoun;Lee, Ho-Yeon;Han, Jiyeon;Yu, Namhee;Ham, Seokjin;Jang, Insoon;Kang, Byunghee;Shin, Sunguk;Kim, Lian;Lee, Seung-Won;Nam, Dougu;Kim, Jihyun F.;Kim, Namshin;Kim, Seon-Young;Lee, Sanghyuk;Roh, Tae-Young;Lee, Byungwook
    • Genomics & Informatics
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    • v.18 no.1
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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/.

Development of a Meta-Information System for Microbial Resources

  • Yu Jae-Woo;Chung Won-Hyong;Sohn Tae-Kwon;Park Yong-Ha;Kim Hong-Ik
    • Journal of Microbiology and Biotechnology
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    • v.16 no.2
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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.