• 제목/요약/키워드: High-throughput structure determination

검색결과 4건 처리시간 0.014초

Structure-based Functional Discovery of Proteins: Structural Proteomics

  • Jung, Jin-Won;Lee, Weon-Tae
    • BMB Reports
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    • 제37권1호
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    • pp.28-34
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    • 2004
  • The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

e-Science Technologies in Synchrotron Radiation Beamline - Remote Access and Automation (A Case Study for High Throughput Protein Crystallography)

  • Wang Xiao Dong;Gleaves Michael;Meredith David;Allan Rob;Nave Colin
    • Macromolecular Research
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    • 제14권2호
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    • pp.140-145
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    • 2006
  • E-science refers to the large-scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. The Grid is a service-oriented architecture proposed to provide access to very large data collections, very large scale computing resources and remote facilities. Web services, which are server applications, enable online access to service providers. Web portal interfaces can further hide the complexity of accessing facility's services. The main use of synchrotron radiation (SR) facilities by protein crystallographers is to collect the best possible diffraction data for reasonably well defined problems. Significant effort is therefore being made throughout the world to automate SR protein crystallography facilities so scientists can achieve high throughput, even if they are not expert in all the techniques. By applying the above technologies, the e-HTPX project, a distributed computing infrastructure, was designed to help scientists remotely plan, initiate and monitor experiments for protein crystallographic structure determination. A description of both the hardware and control software is given together in this paper.

The future of bioinformntics

  • Gribskov, Michael
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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    • pp.1-1
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    • 2003
  • It is clear that computers will play a key role in the biology of the future. Even now, it is virtually impossible to keep track of the key proteins, their names and associated gene names, physical constants(e.g. binding constants, reaction constants, etc.), and hewn physical and genetic interactions without computational assistance. In this sense, computers act as an auxiliary brain, allowing one to keep track of thousands of complex molecules and their interactions. With the advent of gene expression array technology, many experiments are simply impossible without this computer assistance. In the future, as we seek to integrate the reductionist description of life provided by genomic sequencing into complex and sophisticated models of living systems, computers will play an increasingly important role in both analyzing data and generating experimentally testable hypotheses. The future of bioinformatics is thus being driven by potent technological and scientific forces. On the technological side, new experimental technologies such as microarrays, protein arrays, high-throughput expression and three-dimensional structure determination prove rapidly increasing amounts of detailed experimental information on a genomic scale. On the computational side, faster computers, ubiquitous computing systems, high-speed networks provide a powerful but rapidly changing environment of potentially immense power. The challenges we face are enormous: How do we create stable data resources when both the science and computational technology change rapidly? How do integrate and synthesize information from many disparate subdisciplines, each with their own vocabulary and viewpoint? How do we 'liberate' the scientific literature so that it can be incorporated into electronic resources? How do we take advantage of advances in computing and networking to build the international infrastructure needed to support a complete understanding of biological systems. The seeds to the solutions of these problems exist, at least partially, today. These solutions emphasize ubiquitous high-speed computation, database interoperation, federation, and integration, and the development of research networks that capture scientific knowledge rather than just the ABCs of genomic sequence. 1 will discuss a number of these solutions, with examples from existing resources, as well as area where solutions do not currently exist with a view to defining what bioinformatics and biology will look like in the future.

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드론 영상을 이용한 케나프(Hibiscus cannabinus L.) 작물 높이의 노지 표현형 분석 (Field Phenotyping of Plant Height in Kenaf (Hibiscus cannabinus L.) using UAV Imagery)

  • 장규진;김재영;김동욱;정용석;김학진
    • 한국작물학회지
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    • 제67권4호
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    • pp.274-284
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    • 2022
  • 국내 환경에 적합한 케나프 육종을 위해선 비용, 정확도, 속도가 최적으로 설계된 정량적인 고속탐색법(high-throughput)에 기반한 표현형 분석법이 필요하다. 최근 UAV 기반의 원격탐사 기법의 발달로 노지에서 재배되는 작물의 생육인자들에 대한 대량 데이터를 저비용으로 신속하게 얻을 수 있으며 정확하게 분석하기 위한 연구가 활발하게 진행되고 있다. 본 연구에서는 국내에서 요구되는 케나프의 섬유와 가축 사료로서 육종을 위해 해당 목적과 부합한 케나프 높이를 주요 표현형 인자로 선정하여 UAV-RGB에 SfM 알고리즘 기반의 사진 측량 기술을 적용함으로 높이를 예측하고자 하였다. 기존 방법으로 예측한 작물 높이는 바람에 의한 작물의 흔들림으로 오차가 발생할 수 있으며 키가 2 m 이상 크게 자라 실측도 어려운 문제가 있다. 이러한 문제점을 해결하고자 바람에 흔들리지 않는 일정 높이를 가지는 고정 구조물을 설치하여 기준점을 이용한 모델식으로 기하 보정을 통해 높이 예측성능을 개선하였다. 그 결과 R2는 0.80으로 나타났으며, 보정 전(R2 = 0.80, slope = 0.87, offset = -2.51) 보다 높은 신뢰성(R2 = 0.80, slope = 0.94, offset = -1.62)을 확보하였다. 품종별로 생육단계에 따라 측정한 높이 지도를 통해 얻어진 케나프 키 정보는 품종 별로 유의미한 차이를 보임으로서 해당 방법으로 예측한 케나프 높이가 섬유와 가축 사료 목적의 육종 선발에 활용될 수 있을 것으로 판단하였다.