Information Technology Research (ITR): Building the Tree of Life -- A National Resource for Phyloinformatics and Computational Phylogenetics

信息技术研究(ITR):构建生命之树——系统信息学和计算系统发育学的国家资源

基本信息

  • 批准号:
    0331494
  • 负责人:
  • 金额:
    $ 122.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Cooperative Agreement
  • 财政年份:
    2003
  • 资助国家:
    美国
  • 起止时间:
    2003-10-01 至 2008-09-30
  • 项目状态:
    已结题

项目摘要

This collaborative project aims to establish a national computational resource to move the research community much closer to the realization of the goal of the Tree of Life initiative, namely, to reconstruct the evolutionary history of all organisms. This goal is the computational Grand Challenge of evolutionary biology. Current methods are limited to problems several orders of magnitude smaller, and they fail to provide sufficient accuracy at the high end of their range.The planned resource will be designed as an incubator to promote the development of new ideas for this enormously challenging computational task; it will create a forum for experimentalists, computational biologists, and computer scientists to share data, compare methods, and analyze results, thereby speeding up tool development while also sustaining current biological research projects.The resource will be composed of a large computational platform, a collection of interoperable high-performance software for phylogenetic analysis, and a large database of datasets, both real and simulated, and their analyses; it will be accessible through any Web browser by developers, researchers, and educators. The software, freely available in source form, will be usable on scales varying from laptops to high-performance, Grid-enabled, compute engines such as this project's platform, and will be packaged to be compatible with current popular tools. In order to build this resource, this collaborative project will support research programs in phyloinformatics (databases to store multilevel data with detailed annotations and to support complex, tree-oriented queries), in optimization algorithms, Bayesian inference, and symbolic manipulation for phylogeny reconstruction, and in simulation of branching evolution at the genomic level, all within the context of a virtual collaborative center.Biology, and phylogeny in particular, have been almost completely redefined by modern information technology, both in terms of data acquisition and in terms of analysis. Phylogeneticists have formulated specific models and questions that can now be addressed using recent advances in database technology and optimization algorithms. The time is thus exactly right for a close collaboration of biologists and computer scientists to address the IT issues in phylogenetics, many of which call for novel approaches, due to a combination of combinatorial difficulty and overall scale. The project research team includes computer scientists working in databases, algorithm design, algorithm engineering, and high-performance computing, evolutionary biologists and systematists, bioinformaticians, and biostatisticians, with a history of successful collaboration and a record of fundamental contributions, to provide the required breadth and depth.This project will bring together researchers from many areas and foster new types of collaborations and new styles of research in computational biology; moreover, the interaction of algorithms, databases, modeling, and biology will give new impetus and new directions in each area. It will help create the computational infrastructure that the research community will use over the next decades, as more whole genomes are sequenced and enough data are collected to attempt the inference of the Tree of Life. The project will help evolutionary biologists understand the mechanisms of evolution, the relationships among evolution, structure, and function of biomolecules, and a host of other research problems in biology, eventually leading to major progress in ecology, pharmaceutics, forensics, and security. The project will publicize evolution, genomics, and bioinformatics through informal education programs at museum partners of the collaborating institutions. It also will motivate high-school students and college undergraduates to pursue careers in bioinformatics. The project provides an extraordinary opportunity to train students, both undergraduate and graduate, as well as postdoctoral researchers, in one of the most exciting interdisciplinary areas in science. The collaborating institutions serve a large number of underrepresented groups and are committed to increasing their participation in research.
该合作项目旨在建立一个国家计算资源,使研究界更接近实现生命之树计划的目标,即重建所有生物体的进化历史。这个目标是进化生物学的计算大挑战。当前的方法仅限于解决小几个数量级的问题,并且无法在其范围的高端提供足够的精度。计划的资源将被设计为孵化器,以促进针对这一极具挑战性的计算任务的新想法的开发;它将为实验学家、计算生物学家和计算机科学家创建一个论坛,以共享数据、比较方法和分析结果,从而加快工具开发,同时维持当前的生物研究项目。该资源将由一个大型计算平台、用于系统发育分析的可互操作的高性能软件的集合,以及一个包含真实和模拟数据集及其分析的大型数据库;开发人员、研究人员和教育工作者可以通过任何 Web 浏览器访问它。该软件以源代码形式免费提供,可在从笔记本电脑到高性能、支持网格的计算引擎(例如该项目的平台)等各种规模上使用,并将打包为与当前流行的工具兼容。为了构建这一资源,该合作项目将支持系统信息学(存储带有详细注释的多级数据并支持复杂的、面向树的查询的数据库)、优化算法、贝叶斯推理和用于系统发育重建的符号操作的研究项目,以及在基因组水平上模拟分支进化,所有这些都在虚拟协作中心的背景下进行。现代信息技术几乎完全重新定义了生物学,特别是系统发育学,无论是在数据采集方面并在分析方面。系统发生学家已经制定了具体的模型和问题,现在可以使用数据库技术和优化算法的最新进展来解决这些模型和问题。因此,现在正是生物学家和计算机科学家密切合作解决系统发育学中的 IT 问题的最佳时机,由于组合难度和整体规模的结合,其中许多问题需要新颖的方法。该项目研究团队包括从事数据库、算法设计、算法工程和高性能计算工作的计算机科学家、进化生物学家和系统学家、生物信息学家和生物统计学家,他们具有成功合作的历史和基础贡献的记录,以提供所需的信息。该项目将汇集来自多个领域的研究人员,并促进计算生物学领域的新型合作和新研究风格;此外,算法、数据库、建模和生物学的相互作用将为每个领域带来新的动力和新的方向。 它将有助于创建研究界在未来几十年内将使用的计算基础设施,因为更多的全基因组被测序并收集了足够的数据来尝试生命之树的推断。该项目将帮助进化生物学家了解进化机制,生物分子进化、结构和功能之间的关系,以及生物学中的许多其他研究问题,最终导致生态学、药剂学、法医学和安全方面的重大进展。该项目将通过合作机构的博物馆合作伙伴的非正式教育项目来宣传进化论、基因组学和生物信息学。它还将激励高中生和大学本科生从事生物信息学职业。该项目为在科学界最令人兴奋的跨学科领域之一培训本科生和研究生以及博士后研究人员提供了绝佳的机会。合作机构为大量代表性不足的群体提供服务,并致力于增加他们对研究的参与。

项目成果

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会议论文数量(0)
专利数量(0)

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Satish Rao其他文献

Faster shortest-path algorithms for planar graphs
更快的平面图最短路径算法
  • DOI:
    10.1145/195058.195092
  • 发表时间:
    1994-05-23
  • 期刊:
  • 影响因子:
    0
  • 作者:
    P. Klein;Satish Rao;Monika Henzinger;Sairam Subramanian
  • 通讯作者:
    Sairam Subramanian
Using Max Cut to Enhance Rooted Trees Consistency
使用 Max Cut 增强有根树的一致性
Molecular characterization and clinical significance of extraintestinal pathogenic Escherichia coli recovered from a south Indian tertiary care hospital.
从印度南部三级护理医院回收的肠外致病性大肠杆菌的分子特征和临床意义。
  • DOI:
    10.1016/j.micpath.2016.03.001
  • 发表时间:
    2016-06-01
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Arindam Chakraborty;P. Adhikari;S. Shenoy;Satish Rao;B. Dhanashree;V. Saralaya
  • 通讯作者:
    V. Saralaya
What Would Edmonds Do? Augmenting Paths and Witnesses for Degree-Bounded MSTs
埃德蒙兹会做什么?
  • DOI:
    10.1007/s00453-007-9115-5
  • 发表时间:
    2009-05-22
  • 期刊:
  • 影响因子:
    1.1
  • 作者:
    Kamalika Chaudhuri;Satish Rao;Samantha J. Riesenfeld;Kunal Talwar
  • 通讯作者:
    Kunal Talwar
A rigorous analysis of population stratification with limited data
用有限的数据对人口分层进行严格分析
  • DOI:
  • 发表时间:
    2007-01-07
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kamalika Chaudhuri;E. Halperin;Satish Rao;Shuheng Zhou
  • 通讯作者:
    Shuheng Zhou

Satish Rao的其他文献

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{{ truncateString('Satish Rao', 18)}}的其他基金

AF: Small: Algorithms March on through Continuous and Combinatorial Methods
AF:小:算法通过连续和组合方法前进
  • 批准号:
    1816861
  • 财政年份:
    2018
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Standard Grant
AF: Small: Algorithms: approximate, combinatorial, and continuous.
AF:小:算法:近似、组合和连续。
  • 批准号:
    1528174
  • 财政年份:
    2015
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Standard Grant
AitF: Full: Collaborative Research: Graph-theoretic algorithms to improve phylogenomic analyses
AitF:完整:协作研究:改进系统发育分析的图论算法
  • 批准号:
    1535989
  • 财政年份:
    2015
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Standard Grant
AF: Small: Algorithms: Linear, Spectral, and Approximation.
AF:小:算法:线性、谱和近似。
  • 批准号:
    1118083
  • 财政年份:
    2011
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Standard Grant
III: Medium: Collaborative Research: Geometric Network Analysis Tools: Algorithmic Methods for Identifying Structure in Large Informatics Graphs
III:媒介:协作研究:几何网络分析工具:识别大型信息学图中结构的算法方法
  • 批准号:
    0963904
  • 财政年份:
    2010
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Continuing Grant
Explorations in Algorithms
算法探索
  • 批准号:
    0830797
  • 财政年份:
    2008
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Continuing Grant
Collaborative Research: Spectral Graph Theory and Its Applications
合作研究:谱图理论及其应用
  • 批准号:
    0635357
  • 财政年份:
    2007
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Continuing Grant
Metric embeddings, approximation and combinatorial algorithms.
度量嵌入、近似和组合算法。
  • 批准号:
    0515304
  • 财政年份:
    2005
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Continuing Grant
Network Algorithms: Scheduling and Routing
网络算法:调度和路由
  • 批准号:
    0105533
  • 财政年份:
    2001
  • 资助金额:
    $ 122.97万
  • 项目类别:
    Continuing Grant

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