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Unified data resource for NMR spectral and PDB data via and enhanced deposition visualisation and validation autodep system development

Unified data resource for NMR spectral and PDB data via and enhanced deposition visualisation and validation autodep system development
通过增强的沉积可视化和验证 autodep 系统开发,统一 NMR 光谱和 PDB 数据的数据资源
批准号:
BB/E007511/1
负责人:
Gerard Kleywegt
金额:
$58.83万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2007
资助国家:
英国
项目状态:
已结题
起止时间:
2007 至 --

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中文摘要
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英文摘要
The goal of this proposal is to ensure that NMR investigators in Europe have access to a convenient local system of deposition of NMR structures and all associated data in a manner similar to that developed by the RCSB and BMRB in the United States. We will build on our well-established database systems, and we plan to use our infrastructure by building on top of this for NMR Spectral data deposition and retrieval. We have developed web based Java/XML deposition systems, AutoDep4 for the PDB and the EmDep for EMDB and from this base we will extend these systems to allow for the archival and routing of 3D structure data to both the PDB for coordinate information and to the BMRB for NMR spectral data. In addition as a member of the wwPDB the MSD group is committed to process a greater proportion of PDB submissions as part of the global partnership. NMR data contains a wealth of information about the structure and dynamics of biological macromolecules. It is, however, often difficult to extract this information in a meaningful way. For example, the chemical shift values of certain protein backbone atoms can be directly used to determine the secondary structure of a protein, but because chemical shift values are averaged between all the different conformations a molecule adopts the chemical shifts of more flexible backbone regions or side chain atoms are much harder to interpret. In addition, information about, for example, the width of NMR signals is seldom used in solution NMR. The current deposition system presents a number of major difficulties for both depositors and potential users of NMR spectral data. For most depositors, coordinates and spectral data are deposited semi-independently of one another in order to archive a set of experiments. In particular, the time-consuming process of entering metadata related to the experiment must be performed twice, through two different processes, each of which collects a different subset of the relevant experimental data. For potential users of coordinate data the linkage to NMR spectral data there is no simple display option to view such data over the web. We will also extend the functionality of our visualisation and analysis software for molecular structures, AstexViewer@MSD-EBI, for the display and analysis of NMR data in relation to 3D structure and chemical properties to give a fast, object-based access to complex analyses. By enhancing these existing tools, tuned to specific NMR applications, we will provide powerful applications for the NMR structural community. The MSD database contains NMR information that is directly linked to the structure coordinates of biological macromolecules and opens exciting prospects for being able to relate NMR data to the structures in a more meaningful way. In particular from a structure point of view, the restraints are crucial and to visualise the distribution of restraints in relation to structure will be an important deliverable in this proposal. We will carry out a 'large scale' structure related analysis of the spectral data extracted from the BMRB database combining this with specific MSD data on chemical entities in relation to protein chemical shift data. As more relaxation data, which is directly related to the dynamics of the molecule, becomes available it is crucial that large-scale analyses are performed that incorporates as much data as possible. There will be two major results from this grant. First we will have developed a unified deposition interface for the deposition of all data related to macromolecular structure determination by NMR for both PDB specific data and BMRB specific data. Second we will have developed an access portal for the visualisation and analysis of this data suitable for the NMR community to apply to a wide range of problems.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s10858-010-9439-3
发表时间: 2010-10
期刊: Journal of biomolecular NMR
影响因子: 2.7
作者: [Penkett CJ, van Ginkel G, Velankar S, Swaminathan J, Ulrich EL, Mading S, Stevens TJ, Fogh RH, Gutmanas A, Kleywegt GJ, Henrick K, Vranken WF]
通讯作者: Vranken WF
DOI: 10.1016/j.str.2013.07.021
发表时间: 2013-09-03
期刊: STRUCTURE
影响因子: 5.7
作者: [Montelione, Gaetano T., Nilges, Michael, Bax, Ad, Guentert, Peter, Herrmann, Torsten, Richardson, Jane S., Schwieters, Charles D., Vranken, Wim F., Vuister, Geerten W., Wishart, David S., Berman, Helen M., Kleywegt, Gerard J., Markley, John L.]
通讯作者: Markley, John L.
DOI: 10.1002/prot.24213
发表时间: 2013-04
期刊: Proteins
影响因子: 2.9
作者: [Hendrickx PM, Gutmanas A, Kleywegt GJ]
通讯作者: Kleywegt GJ
DOI: 10.1007/s10858-009-9378-z
发表时间: 2009-12
期刊: Journal of biomolecular NMR
影响因子: 2.7
作者: [Doreleijers JF, Vranken WF, Schulte C, Lin J, Wedell JR, Penkett CJ, Vuister GW, Vriend G, Markley JL, Ulrich EL]
通讯作者: Ulrich EL
Public archiving and data integration in the era of multi-modal imaging
  • 批准号:
    MR/P019544/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $120.62万
  • 财政年份:
    2017
  • 负责人:
    Gerard Kleywegt
  • 依托单位:
Supporting archival and dissemination of small-angle scattering data for atomistic structures in the PDB
  • 批准号:
    BB/M020347/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $18.86万
  • 财政年份:
    2015
  • 负责人:
    Gerard Kleywegt
  • 依托单位:
Integrating 3D biological data on scales from molecules to cells
  • 批准号:
    MR/L007835/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $80.36万
  • 财政年份:
    2014
  • 负责人:
    Gerard Kleywegt
  • 依托单位:
CRESTANO - Common REst api for Structural ANnotation
  • 批准号:
    BB/K016970/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $14.99万
  • 财政年份:
    2013
  • 负责人:
    Gerard Kleywegt
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: