• Title/Summary/Keyword: BLAST search

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Design and Implementation of a Web-Based Search Engine for Single Nucleotide Polymorphism Data (웹기반의 Single Nucleotide Polymorphism 데이터 검색 시스템의 설계 및 구현)

  • 양진옥;김상수
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.160-162
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    • 2002
  • SNP는 개인과 개인간의 DNA에 존재하는 한 염기 쌍의 차이(single base-pair variation)이다. SNP를 이용하면 사람마다 다른 유전병의 형태 등을 규명할 수 있다. 본 논문에서는 한국생명공학연구원의 유전체 사업단에서 개발해 오고 있는 웹기반 SNP데이터 검색 시스템의 설계와 구현에 대해서 설명한다. 본 시스템은 일반 속성(attribute)을 저장하고 검색하기 위해 PostgreSQL DBMS를 사용하고, DNA 시퀸스 검색을 위해 BLAST검색엔진을 사용한 약결합 아키텍쳐(loosely-coupled architecture)를 채택하고 있다. 즉, 일반 속성으로 저장될 수 있는 데이터들은 데이터베이스의 테이블들의 컬럼 값으로 저장하고 SQL 언어를 통해 검색할 수 있도록 하였으며, DNA 시퀸스 검색을 위해서는 BLAST에서 제공하는 인덱스를 구축하고 BLAST 명령어를 사용하여 검색할 수 있도록 하였다. 또한, 결과 분석 모듈을 구현하여 검색 결과들이 다른 웹 사이트의 데이터를 가리키도록 하였다.

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The Design and Implementation of a Web-Based Search Engine for GenBank Patent Data (웹기반의 GenBank 특허 데이터 검색 시스템의 설계 및 구현)

  • 양진옥;김상수
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10a
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    • pp.43-45
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    • 2001
  • NCBI 의 GenBank 데이터베이스는 전세계에서 수집된 염기 서열 데이터들의 집합이며, 그 중 특허로 등록되어 있는 데이터들을 GenBank 특허 데이터라 부른다. 본 논문에서는 한국생명공학연구원의 유전체 사업단에서 개발해 오고 있는 웹기반 GenBank 특허 데이터 검색 시스템의 설계와 구현에 대해서 설명한다. 본 시스템은 일반 속성(attribute)을 저장하고 검색하기 위해 DBMS 를 사용하고, DNA 시퀸스 검색을 위해 BLAST를 사용한 약결합 아키텍쳐(loosely-coupled architecture)를 채택하고 있다. 즉, 일반 속성으로 저장될 수 있는 데이터들은 데이터베이스의 테이블들의 컬럼 값으로 저장하고 SQL 언어를 통해 검색할 수 있도록 하였으며, DNA 시퀸스 검색을 위해서는 BLAST 에서 제공하는 인덱스를 구축하고 BLAST 명령어를 사용하여 검색할 수 있도록 하였다. 또한, 검색 결과들이 기존의 외부 특허 시스템과 연동하도록 하기 위해, 결과 분석 모듈을 구현하여 검색 결과들이 다른 웹 사이트의 데이터를 가리키도록 하였다. 마지막으로, 이러한 DNA 검색 시스템을 구현할 때에 고려해 되야 되는 이슈들을 설명한다.

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Algorithm for Predicting Functionally Equivalent Proteins from BLAST and HMMER Searches

  • Yu, Dong Su;Lee, Dae-Hee;Kim, Seong Keun;Lee, Choong Hoon;Song, Ju Yeon;Kong, Eun Bae;Kim, Jihyun F.
    • Journal of Microbiology and Biotechnology
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    • v.22 no.8
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    • pp.1054-1058
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    • 2012
  • In order to predict biologically significant attributes such as function from protein sequences, searching against large databases for homologous proteins is a common practice. In particular, BLAST and HMMER are widely used in a variety of biological fields. However, sequence-homologous proteins determined by BLAST and proteins having the same domains predicted by HMMER are not always functionally equivalent, even though their sequences are aligning with high similarity. Thus, accurate assignment of functionally equivalent proteins from aligned sequences remains a challenge in bioinformatics. We have developed the FEP-BH algorithm to predict functionally equivalent proteins from protein-protein pairs identified by BLAST and from protein-domain pairs predicted by HMMER. When examined against domain classes of the Pfam-A seed database, FEP-BH showed 71.53% accuracy, whereas BLAST and HMMER were 57.72% and 36.62%, respectively. We expect that the FEP-BH algorithm will be effective in predicting functionally equivalent proteins from BLAST and HMMER outputs and will also suit biologists who want to search out functionally equivalent proteins from among sequence-homologous proteins.

Protein Sequence Search based on N-gram Indexing

  • Hwang, Mi-Nyeong;Kim, Jin-Suk
    • Bioinformatics and Biosystems
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    • v.1 no.1
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    • pp.46-50
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    • 2006
  • According to the advancement of experimental techniques in molecular biology, genomic and protein sequence databases are increasing in size exponentially, and mean sequence lengths are also increasing. Because the sizes of these databases become larger, it is difficult to search similar sequences in biological databases with significant homologies to a query sequence. In this paper, we present the N-gram indexing method to retrieve similar sequences fast, precisely and comparably. This method regards a protein sequence as a text written in language of 20 amino acid codes, adapts N-gram tokens of fixed-length as its indexing scheme for sequence strings. After such tokens are indexed for all the sequences in the database, sequences can be searched with information retrieval algorithms. Using this new method, we have developed a protein sequence search system named as ProSeS (PROtein Sequence Search). ProSeS is a protein sequence analysis system which provides overall analysis results such as similar sequences with significant homologies, predicted subcellular locations of the query sequence, and major keywords extracted from annotations of similar sequences. We show experimentally that the N-gram indexing approach saves the retrieval time significantly, and that it is as accurate as current popular search tool BLAST.

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Gene Structure and Phylogenetic Analysis of Cytohesin Family

  • Kim, Heui-Soo;Shin, Kyung-Mi;Lee, Ji-Won;Yi, Joo-Mi
    • Journal of Life Science
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    • v.11 no.1
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    • pp.39-41
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    • 2001
  • Cytohesin family has been thought to participate in inside-outside signaling linking growth factor receptor stimulation of PI 3-kinase to cell adhesion and stimulate nucleotide exchange of ARF through its Sec7 domain. The genomic structure of the cytohesin family was analyzed by BLAST search using cDNA and genomic DNA sequences from the GeneBank database. The cytohesin-2 was encoded by 12 exons. while the cytohesin-4 was encoded by 13 exons. The Sec7 and PH domains were not encoded by separate exons. In an analysis of retroviral integration, those two families did not contain any retroviral elements in introns or exons. The phylogenetic tree calculated by the neighbor-joining method suggests that the cytohesin-1 family was closely related to cytohesin-3 (ARNO3) family. These date could be of great use in further studies for resolving the exact function and evolution of the cytohesin family.

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KRDD: Korean Rice Ds-tagging Lines Database for Rice (Oryza sativa L. Dongjin)

  • Kim, Chang-Kug;Lee, Myung-Chul;Ahn, Byung-Ohg;Yun, Doh-Won;Yoon, Ung-Han;Suh, Seok-Cheol;Eun, Moo-Young;Hahn, Jang-Ho
    • Genomics & Informatics
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    • v.6 no.2
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    • pp.64-67
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    • 2008
  • The Korean Rice Ds-tagging lines Database (KRDD) is designed to provide information about Ac/Ds insertion lines and activation tagging lines using japonica rice. This database has provided information on 18,158 Ds lines, which includes the ID, description, photo image, sequence information, and gene characteristics. The KRDD is visualized using a web-based graphical view, and anonymous users can query and browse the data using the search function. It has four major menus of web pages: (i) a Blast Search menu of a mutant line; Blast from rice Ds-tagging mutant lines; (ii) a primer design tool to identify genotypes of Ds insertion lines; (iii) a Phenotype menu for Ds lines, searching by identification name and phenotype characteristics; and (iv) a Management menu for Ds lines.

Screening of Fruiting Body Formation-Specific Genes from the Medicinal Mushroom Cordyceps militaris MET7903 (약용버섯번데기 동충하초 MET7903의 특이적 자실체형성 유전자의 선별)

  • Yun, Bangung;Chung, Ki-Chul
    • Journal of Mushroom
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    • v.2 no.3
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    • pp.145-148
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    • 2004
  • This study was carried out to screen the fruiting body formation-specific genes from the medicinal mushroom Cordyceps militaris. A cDNA synthesized using total RNA from 4 stages of mushroom development, mycelium, primordium, immature fruiting body and mature fruiting body. Differential expression gene screening was performed by DD-PCR(Differential Display Arbitrary Primer PCR) with cDNA, we sequenced partial 6 genes using pGEM cloning vector. The DNA Sequence of the six DD-PCR products derived from differentially expressed genes was compared to that in the GenBank database by using the NCBI BLAST search to identify similarities to known sequences. Sequence analysis showed that six of DD-PCR products have unknown sequence.

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Depth-first branch-and-bound-based decoder with low complexity (검출 복잡도를 감소 시키는 Depth-first branch and bound 알고리즘 기반 디코더)

  • Lee, Eun-Ju;Kabir, S.M.Humayun;Yoon, Gi-Wan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.12
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    • pp.2525-2532
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    • 2009
  • In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

Monitoring of Commercial Products Sold on Sushi Buffet Restaurants in South Korea using DNA Barcode Information (국내 대형 초밥 뷔페에서 사용되는 수산물의 원재료 모니터링 연구)

  • Kang, Tae Sun
    • Journal of Food Hygiene and Safety
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    • v.35 no.1
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    • pp.45-50
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    • 2020
  • In this study, seafood products (n=26) sold on sushi buffet restaurants in the city of Wonju were monitored by analyzing sequences of DNA barcode markers (cytochrome c oxidase subunit I and 16S ribosomal RNA genes). NCBI BLAST database was screened with the barcode sequences analyzed as a query for species identification. The BLAST search revealed that fifteen samples (58%) analyzed were consistent with their labeling information; however, the ingredients used in seven samples (27%) were not compliant with their label information. In the case of these mislabeled products, ingredients for sutchi catfish sushi and cherry bass sashimi were identified as Pangasianodon hypophthalmus and Lampris guttatus, respectively. For Japanese flying-fish roe sushi and Pacific herring roe sushi, roe of Mallotus villosus was used as an ingredient. Amphioctopus fangsiao and A. membranaceus were used in octopus sushi and soybean-marinated squid products, respectively. This monitoring result can contribute to the protection of consumer rights and the reduction of fraudulent practices in the food industry.

A Performance Comparison of Protein Profiles for the Prediction of Protein Secondary Structures (단백질 이차 구조 예측을 위한 단백질 프로파일의 성능 비교)

  • Chi, Sang-Mun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.1
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    • pp.26-32
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    • 2018
  • The protein secondary structures are important information for studying the evolution, structure and function of proteins. Recently, deep learning methods have been actively applied to predict the secondary structure of proteins using only protein sequence information. In these methods, widely used input features are protein profiles transformed from protein sequences. In this paper, to obtain an effective protein profiles, protein profiles were constructed using protein sequence search methods such as PSI-BLAST and HHblits. We adjust the similarity threshold for determining the homologous protein sequence used in constructing the protein profile and the number of iterations of the profile construction using the homologous sequence information. We used the protein profiles as inputs to convolutional neural networks and recurrent neural networks to predict the secondary structures. The protein profile that was created by adding evolutionary information only once was effective.