• Title/Summary/Keyword: sequence database

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A Unified Object Database for Biochemical Pathways

  • Jung, T.S.;Oh, J.S.;Jang, H.K.;Ahn, M.S.;Roh, D.H.;Cho, W.S.
    • 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.

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A Head Gesture Recognition Method based on Eigenfaces using SOM and PRL (SOM과 PRL을 이용한 고유얼굴 기반의 머리동작 인식방법)

  • Lee, U-Jin;Gu, Ja-Yeong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.3
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    • pp.971-976
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    • 2000
  • In this paper a new method for head gesture recognition is proposed. A the first stage, face image data are transformed into low dimensional vectors by principal component analysis (PCA), which utilizes the high correlation between face pose images. The a self organization map(SM) is trained by the transformed face vectors, in such a that the nodes at similar locations respond to similar poses. A sequence of poses which comprises each model gesture goes through PCA and SOM, and the result is stored in the database. At the recognition stage any sequence of frames goes through the PCA and SOM, and the result is compared with the model gesture stored in the database. To improve robustness of classification, probabilistic relaxation labeling(PRL) is used, which utilizes the contextural information imbedded in the adjacent poses.

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Performance Improvement of BLAST using Grid Computing and Implementation of Genome Sequence Analysis System (그리드 컴퓨팅을 이용한 BLAST 성능개선 및 유전체 서열분석 시스템 구현)

  • Kim, Dong-Wook;Choi, Han-Suk
    • The Journal of the Korea Contents Association
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    • v.10 no.7
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    • pp.81-87
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    • 2010
  • This paper proposes a G-BLAST(BLAST using Grid Computing) system, an integrated software package for BLAST searches operated in heterogeneous distributed environment. G-BLAST employed 'database splicing' method to improve the performance of BLAST searches using exists computing resources. G-BLAST is a basic local alignment search tool of DNA Sequence using grid computing in heterogeneous distributed environment. The G-BLAST improved the existing BLAST search performance in gene sequence analysis. Also G-BLAST implemented the pipeline and data management method for users to easily manage and analyze the BLAST search results. The proposed G-BLAST system has been confirmed the speed and efficiency of BLAST search performance in heterogeneous distributed computing.

Feature Selection-based Voice Transformation (단위 선택 기반의 음성 변환)

  • Lee, Ki-Seung
    • The Journal of the Acoustical Society of Korea
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    • v.31 no.1
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    • pp.39-50
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    • 2012
  • A voice transformation (VT) method that can make the utterance of a source speaker mimic that of a target speaker is described. Speaker individuality transformation is achieved by altering three feature parameters, which include the LPC cepstrum, pitch period and gain. The main objective of this study involves construction of an optimal sequence of features selected from a target speaker's database, to maximize both the correlation probabilities between the transformed and the source features and the likelihood of the transformed features with respect to the target model. A set of two-pass conversion rules is proposed, where the feature parameters are first selected from a database then the optimal sequence of the feature parameters is then constructed in the second pass. The conversion rules were developed using a statistical approach that employed a maximum likelihood criterion. In constructing an optimal sequence of the features, a hidden Markov model (HMM) was employed to find the most likely combination of the features with respect to the target speaker's model. The effectiveness of the proposed transformation method was evaluated using objective tests and informal listening tests. We confirmed that the proposed method leads to perceptually more preferred results, compared with the conventional methods.

Analysis of Expressed Sequence Tags from the Antarctic Psychrophilic Green Algae, Pyramimonas gelidicola

  • Jung, Woongsic;Lee, Sung Gu;Kang, Se Won;Lee, Yong Seok;Lee, Jun Hyuck;Kang, Sung-Ho;Jin, Eon Seon;Kim, Hak Jun
    • Journal of Microbiology and Biotechnology
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    • v.22 no.7
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    • pp.902-906
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    • 2012
  • Expressed sequence tags (ESTs) from the Antarctic green algae Pyramimonas gelidicola were analyzed to obtain molecular information on cold acclimation of psychrophilic microorganisms. A total of 2,112 EST clones were sequenced, generating 222 contigs and 219 singletons, and 200 contigs and 391 singletons from control ($4^{\circ}C$) and cold-shock conditions ($-2^{\circ}C$), respectively. The complete EST sequences were deposited to the DDBJ EST database (http://www.ddbj.nig.ac.jp/index-e.html) and the nucleotide sequences reported in this study are available in the DDBJ/EMBL/GenBank. These EST databases of Antarctic green algae can be used in a wide range of studies on psychrophilic genes expressed by polar microorganisms.

Human Proteome Data Analysis Protocol Obtained via the Bacterial Proteome Analysis

  • Kwon, Kyung-Hoon;Park, Gun-Wook;Kim, Jin-Young;Lee, Jeong-Hwa;Kim, Seung-Il;Yoo, Jong-Shin
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.91-95
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    • 2005
  • In the multidimensional protein identification technology of high-throughput proteomics, we use one-dimensional gel electrophoresis and after the separation by two-dimensional liquid chromatography, the sample is analyzed by tandem mass spectrometry. In this study, we have analyzed the Pseudomonas Putida KT2440 protein. From the protein identification, the protein database was combined with its reversed sequence database. From the peptide selection whose error rate is less than 1%, the SEQUEST database search for the tandem mass spectral data identified 2,045 proteins. For each protein, we compared the molecular weight calibrated from 1D-gel band position with the theoretical molecular weight computed from the amino acid sequence, by defining a variable MW$_{corr}$ Since the bacterial proteome is simpler than human proteome considering the complexity and modifications, the proteome analysis result for the Pseudomonas Putida KT2440 could suggest a guideline to build the protocol to analyze human proteome data.

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A data management system for microbial genome projects

  • Ki-Bong Kim;Hyeweon Nam;Hwajung Seo and Kiejung Park
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2000.11a
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    • pp.83-85
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    • 2000
  • A lot of microbial genome sequencing projects is being done in many genome centers around the world, since the first genome, Haemophilus influenzae, was sequenced in 1995. The deluge of microbial genome sequence data demands new and highly automatic data flow system in order for genome researchers to manage and analyze their own bulky sequence data from low-level to high-level. In such an aspect, we developed the automatic data management system for microbial genome projects, which consists mainly of local database, analysis programs, and user-friendly interface. We designed and implemented the local database for large-scale sequencing projects, which makes systematic and consistent data management and retrieval possible and is tightly coupled with analysis programs and web-based user interface, That is, parsing and storage of the results of analysis programs in local database is possible and user can retrieve the data in any level of data process by means of web-based graphical user interface. Contig assembly, homology search, and ORF prediction, which are essential in genome projects, make analysis programs in our system. All but Contig assembly program are open as public domain. These programs are connected with each other by means of a lot of utility programs. As a result, this system will maximize the efficiency in cost and time in genome research.

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Partial Sequence Analysis of Puumala Virus M Segment from Bats in Korea

  • Yun, Bo-Kyoung;Yoon, Jeong-Joong;Lee, Yun-Tai
    • The Journal of Korean Society of Virology
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    • v.29 no.1
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    • pp.23-31
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    • 1999
  • Hantavirus is a genus of the Bunyaviridae family causing two serious diseases, hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS). Puumala virus is a member of hantavirus originally found in Europe, and its natural reservoir is Clethrionomys glareolus. It is also associated with the human disease nephropathia epidemica, a milder form of HFRS. To identify the hantaviruses in bats, bats were collected from Jeong-Sun, Won-Joo, Chung-Ju and Hwa-Cheon area in Korea, and nested RT-PCR was performed with serotype specific primer from M segment. Interestingly, Puumala virus was detected in bats (Rhinolophus ferrum-equinum) only from Won-Joo. The 327 bp nested RT-PCR product, was sequenced. The sequence database search indicates that the sequence is homologous to the published sequence of Puumala viruses. The sequence similarities were ranged from 71% to 97%. The highest sequence similarity was 97% with Puumala virus Vranicam strain, and the lowest was 71% with Puumala virus K27 isolate. Puumala virus Vranicam strain was isolated from a bank vole (Clethrionomys glareolus) in Bosnia-Hercegovina. Puumala virus K27 was isolated from human in Russia. This analysis confirms that bats (Rhinolophus ferrum-equinum) in Korea are natural reservoir of Puumala virus.

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A Study on Spatial Scheduling in the P.E. Stage (선행 탑재장에서의 공간일정계획에 관안 연구)

  • Koo Chung-kon;Yoon Duck-Young;Bae Tae-Kyu;Cho Min-Ch
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2004.05a
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    • pp.61-66
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    • 2004
  • In this paper an effort is made to develop an innovative spatial arrangement concept pertaining to ship building industry. The spatial scheduling is the problem that concentrates on effective planning of available space and arrangements of blocks and in a priority manner. In order to create an effective spatial scheduling. a database providing the priority has to be available to make the erection sequence. Such a system works hand in hand with erection sequence generator program The erection sequence program works on the conventional network analysis method which uses a typical parent-children idea for the calculation of the ENT(possible earliest network start time) and LNT(possible latest network start time). This program works in a cyclic manner taking turns by calculating the ENT in upward trace and LNT on the return trace thereby generating the entire erection sequence diagram for the requisite problem The generated database serves as an input data for spatial scheduling problem. When the system works it takes into consideration the entire system based on heuristic concepts as mentioned. There system uses the spatial aspects such as the available area of the P. E area and plan area of the corresponding blocks and its priority of erection from the erection sequence generator program develops the spatial scheduling arrangement. In this paper using all these concepts an innovative spatial schedule development system developed.

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An Efficient Algorithm for Similarity Search in Large Biosequence Database (대용량 유전체를 위한 효율적인 유사성 검색 알고리즘)

  • Jeong, In-Seon;Park, Kyoung-Wook;Lim, Hyeong-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.1073-1076
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    • 2005
  • Since the size of biosequence database grows exponentially every year, it becomes impractical to use Smith-Waterman algorithm for exact sequence similarity search. For fast sequence similarity search, researchers have been proposed heuristic methods that use the frequency of characters in subsequences. These methods have the defect that different sequences are treated as the same sequence. Because of using only the frequency of characters, the accuracy of these methods are lower than Smith-Waterman algorithm. In this paper, we propose an algorithm which processes query efficiently by indexing the frequency of characters including the positional information of characters in subsequences. The experiments show that our algorithm improve the accuracy of sequence similarity search approximately 5${\sim}$20% than heuristic algorithms using only the frequency of characters.

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