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Discovery of Complex Recurring Protein Interaction Patterns within Interactomes: Algorithms, Applications and Software

Discovery of Complex Recurring Protein Interaction Patterns within Interactomes: Algorithms, Applications and Software
相互作用组中复杂重复蛋白质相互作用模式的发现:算法、应用程序和软件
批准号:
0850063
负责人:
Mona Singh
金额:
$61.3万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-01 至 2013-08-31

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中文摘要
翻译
向普林斯顿大学提供了一笔赠款,用于开发计算工具,通过发现和分析蛋白质等生物单位之间反复出现的关系模式,促进生物网络的研究。搜索生物数据中的重复模式一直是计算生物学中许多研究和分析的支柱,并且对于揭示生物功能至关重要。在过去的几年里,蛋白质-蛋白质相互作用数据的可用性出现了爆炸性的增长,我们现在已经有了大规模的人类和许多模型生物的相互作用网络。本研究的总体目标是开发必要的计算基础设施,以便将循环模式分析应用于生物网络-它已经被证明在分析生物序列、结构和表达数据方面是有用的-。这项研究的具体目标是:(1)开发一个计算框架,以揭示哪些类型的蛋白质优先共同工作,目的是揭示潜在的细胞组织和蛋白质功能的模式。(2)将这些算法应用于整个进化范围内现有的相互作用网络,目的是了解生物体内重复出现的网络单位是如何不同的,并揭示新类型的蛋白质是如何合并到现有网络中的。(3)开发软件,在给定特定蛋白质序列的情况下,揭示其参与的重复网络相互作用模式,目标是将输入蛋白质置于其细胞路径和模块的上下文中,从而深入了解其功能。这项拟议的研究与生物信息学新本科课程的开发相结合,最终项目侧重于网络分析。该项目的软件和结果将从网站http://compbio.cs.princeton.edu.上获得
英文摘要
A grant has been awarded to Princeton University to develop computational tools to facilitate research in biological networks through discovery and analysis of recurring patterns of relations among biological units such as proteins. Searching for recurring patterns in biological data has been the backbone of much research and analysis in computational biology, and has been essential in uncovering biological function. In the last few years, there has been an explosion in the availability of protein-protein interaction data, and we now have large-scale interaction networks for human and many model organisms.The overall goal of this research is to develop the necessary computational infrastructure for applying recurring pattern analysis---which has already proven to be useful in analyzing biological sequence, structure and expression data---to biological networks. The specific goals of this research are: (1) To develop a computational framework for uncovering what types of proteins preferentially work together, with the goal of revealing patterns underlying cellular organization and protein functioning. (2) To apply these algorithms to existing interaction networks across the evolutionary range, with the goals of understanding how the recurring network units within organisms differ and of revealing how new types of proteins are incorporated into existing networks. (3) To develop software that, given a particular protein sequence, uncovers the recurring network interaction patterns it participates in, with the goal of placing the input protein within the context of its cellular pathways and modules, and thereby gaining insight into its function. The proposed research is coupled with the development of a new undergraduate course in bioinformatics, with a final project focusing on network analysis. Software and results of this project will be available from the website http://compbio.cs.princeton.edu.
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Student Support RECOMB 2016
  • 批准号:
    1602100
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.5万
  • 财政年份:
    2016
  • 负责人:
    Mona Singh
  • 依托单位:
ABI: Innovation: Computationally uncovering dynamic transcription factor interactions within and across organisms
  • 批准号:
    1458457
  • 项目类别:
    Standard Grant
  • 资助金额:
    $70.75万
  • 财政年份:
    2015
  • 负责人:
    Mona Singh
  • 依托单位:
Student Support for Recomb 2013
  • 批准号:
    1328201
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.7万
  • 财政年份:
    2013
  • 负责人:
    Mona Singh
  • 依托单位:
Recomb Special Session: Computational Challenges and Emerging Areas within Computational Biology
  • 批准号:
    1152312
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.1万
  • 财政年份:
    2011
  • 负责人:
    Mona Singh
  • 依托单位:
国内基金
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  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    赵锐
  • 依托单位:
线粒体参与呼吸中枢pre-Bötzinger complex呼吸可塑性调控的机制研究