• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.153-160
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• 2006

Brassica rape is an important species used as a vegetable, oil, and fodder worldwide. It is related phylogenically to Arabidopsis thaliana, which has already been fully sequenced as a model plant. The 'Multinational Brassica Genome Project (MBGP)'was launched by the international Brassica community with the aim of sequencing the whole genome of B. rapa in 2003 on account of its value and the fact that it has the smallest genome among the diploid Brassica. The genome study was carried out not only to know the structure of genome but also to understand the function and the evolution of the genes comprehensively. There are two mapping populations, over 1,000 molecular markers and a genetic map, 2 BAC libraries, physical map, a 22 cDHA libraries as suitable genomic materials for examining the genome of B. rapa ssp. pekinensis Chinese cabbage. As the first step for whole genome analysis, 220,000 BAC-end sequences of the KBrH and KBrB BAC library are achieved by cooperation of six countries. The results of BAC-end sequence analysis will provide a clue in understanding the structure of the genome of Brassica rapa by analyzing the gene sequence, annotation and abundant repetitive DHA. The second stage involves sequencing of the genetically mapped seed BACs and identifying the overlapping BACs for complete genome sequencing. Currently, the second stage is comprises of process genetic anchoring using communal populations and maps to identify more than 1,000 seed BACs based on a BAC-to-BAC strategy. For the initial sequencing, 629 seed BACs corresponding to the minimum tiling path onto Arabidopsis genome were selected and fully sequenced. These BACs are now anchoring to the genetic map using the development of SSR markers. This information will be useful for identifying near BAC clones with the seed BAC on a genome map. From the BAC sequences, it is revealed that the Brassica rapa genome has extensive triplication of the DNA segment coupled with variable gene losses and rearrangements within the segments. This article introduces the current status and prospective of Korea Brassica Genome Project and the bioinformatics tools possessed in each national team. In the near future, data of the genome will contribute to improving Brassicas for their economic use as well as in understanding the evolutional process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.466-472
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• 2017

This study was designed to examine the diversity census of fungi in rumen microbiome via meta-analysis of fungal 28S rDNA sequences. Both terms, "rumen" and "ruminal," were searched to retrieve the sequences of rumen fungi. As of September 2016, these sequences (n=165) of ruminal origin were retrieved from the Ribosomal Database Project (RDP; http://rdp.cme.msu.edu), an archive of all 28S rDNA sequences and were assigned to the phyla Ascomycota, Neocallimastigomycota, and Basidiomycota, which accounted for 109, 48, and 8 of the 165 sequences, respectively. Ascomycota sequences were assigned to the genera Pseudonectria, Magnaporthe, Alternaria, Cochliobolus, Cladosporium, and Davidiella, including fungal plant pathogens or mycotoxigenic species. Moreover, Basidiomycota sequences were assigned to the genera Thanatephorus and Cryptococcus, including fungal plant pathogens. Furthermore, Neocallimastigomycota sequences were assigned to the genera Cyllamyces, Neocallimastix, Anaeromyces, Caecomyces, Orpinomyces, and Piromyces, which may degrade the major structural carbohydrates of the ingested plant material. This study provided a collective view of the rumen fungal diversity using a meta-analysis of 28S rDNA sequences. The present results will provide a direction for further studies on ruminal fungi and be applicable to the development of new analytic tools.

• Microbiology and Biotechnology Letters
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• v.32 no.3
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• pp.218-223
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• 2004

Myxobacteria are Gram-negative soil bacteria known to be a rich source of potentially useful secondary metabolites. We have isolated 204 strains of bacteriolytic myxobacteria from soil samples collected in Korea and determined their 16S rRNA sequences. Sequence analysis of the partially determined 16S rRNA sequences has suggested that 132 isolates (65% of total isolates) belong to the genus Myxococcus and 59 isolates (29% of total isolates) belong to the genus Corallococcus. Meanwhile, 4 isolates appear to be Archangium spp. and the other 4 isolates appear to be Stigmatella spp. Genera of the remained 5 isolates have not been identified because their 16S rRNA sequences are distantly related to those of known myxobacteria.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.480-488
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• 2002

본 논문에서는 하나의 시스템 안에서 효율적인 유전자 데이터의 관리와 다양한 서열 분석작업이 가능한 기능 유전체학을 지원하는 서열 분석 및 관리 시스템인 GWB(Gene WorkBench)를 설계하고 구현하였다. GWB는 로컬 데이터베이스 관리뿐만 아니라 GenBank, EMBL, SWISSPROT와 같은 외부 공공 데이터베이스에 대한 접근 기능도 제공하며, 권한을 가진 내부 이용자와 그렇지 못한 외부 이용자들을 구분하여 일부 유용한 기능들은 외부 사용자들도 이용할 수 있도록 설계되었다. 또 GWB는 유전자에 관한 문헌정보 검색과 관련 유전자 탐색 기능 등 일부 유전자 기능 연구를 지원하는 기능을 제공하고 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.11-16
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• 2007

최근 컴퓨터를 이용한 유전자 해석 기술이 급속히 발전함에 따라 DNA서열분석도구의 필요성도 늘어나고 있다. 그러나 DNA서열분석에 필요한 데이터베이스는 다양한 형태의 포맷이 제공되어 지고 있고, 유전자 서열 데이터의 처리를 위한 애플리케이션에서도 서로 다른 양식의 포맷이 사용되고 있다. 이로 인해 다른 형태의 포맷이 필요한 경우 별도의 파서를 구현 하는 문제가 발생한다. 이러한 단점을 보안하는 하나의 방법으로 GenBank에서 제공되는 XML파일을 이용한 웹2.0 환경인 RIA(Rich Internet Application)개발방식을 제안한다. RIA개발방식은 XML파서와 XML을 처리할 수 있는 E4X(ECMAScript for XML)와 같은 API를 제공 하여 XML로 리턴 되는 데이터를 쉽게 처리하여 화면으로 보여준다.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.51-62
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• 2005

After figuring out the function of an amino acid sequence, we can infer the function of the other amino acids that have similar sequence composition. Besides, it is possible that we alter protein whose function we know, into useful protein using genetic engineering method. In this process. an original protein amino sequence produces various protein sequences that have different sequence composition. Here, a systematic technique is needed to manage protein version sequences and reference data of those sequences. Thus, in this paper we proposed a technique of managing protein version sequences based on local sequence alignment and a technique of managing protein historical reference data using Trigger This method automatically determines the similarity between an original sequence and each version sequence while the protein version sequences are stored into database. When this technique is employed, the storage space that stores protein sequences is also reduced. After storing the historical information of protein and analyzing the change of protein sequence, we expect that a new useful protein and drug are able to be discovered based on analysis of version sequence.

• KOGO NEWS
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• v.3 no.2
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• pp.7.2-7.2
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• 2003

• KIISE Transactions on Computing Practices
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• v.21 no.3
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• pp.263-268
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• 2015

Malware variations could be defined as malicious executable files that have similar functions but different structures. In order to classify the variations, this paper analyzed sequence alignment, the method used in Bioinformatics. This method found common parts of the Malwares' API call information. This method's performance is dependent on the API call information's length; if the length is too long, the performance should be very poor. Therefore we removed the repeated patterns in API call information in order to improve the performance of sequence alignment analysis, before the method was applied. Finally the similarity between malware was analyzed using sequence alignment. The experimental results with the real malware samples were presented.

• Korean Journal of Microbiology
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• v.39 no.2
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• pp.67-75
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• 2003

One large topic in comparative genomics is to predict functional annotation by classifying protein sequences. Computational approaches for function prediction include protein structure prediction, sequence alignment and domain prediction or binding site prediction. This paper is on another computational approach searching for sets of homologous sequences from sequence similarity graph. Methods based on similarity graph do not need previous knowledges about sequences, but largely depend on the researcher's subjective threshold settings. In this paper, we propose a genome sequence clustering method of iterative testing and graph decomposition, and a simple method to calculate a strict threshold having biochemical meaning. Proposed method was applied to known bacterial genome sequences and the result was shown with the BAG algorithm's. Result clusters are lacking some completeness, but the confidence level is very high and the method does not need user-defined thresholds.

• Smart Media Journal
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• v.2 no.4
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• pp.34-40
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• 2013

Rapid sequencing of individual genomes with next generation sequencer opens new horizon to biology and personalized medicine. The analyzed sequences help to check several genomic abnormality, genomic expression, epigenomic phenotypes, gene annotation after assembly of their reads. Several trials integrating genomic information and clinical data will assist disease diagnostics and clinical treatments. To have a large step towards individualized medicine, development of smart interface linking specialized sequence data to the public is necessary.