Information Technology Research (ITR): Building the Tree of Life -- A National Resource for Phyloinformatics and Computational Phylogenetics
Information Technology Research (ITR): Building the Tree of Life -- A National Resource for Phyloinformatics and Computational Phylogenetics
批准号:
0331495
负责人:
Max Gunzburger
金额:
$0.0万
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
项目状态:
已结题
起止时间:
2003-10-01 至 2010-09-30
中文摘要
这一合作项目旨在建立一个国家计算资源,使研究界更接近于实现生命之树倡议的目标,即重建所有生物体的进化史。这个目标是进化生物学的计算大挑战。目前的方法仅限于小几个数量级的问题,在其范围的高端无法提供足够的精度,计划中的资源将被设计为孵化器,以促进为这一极具挑战性的计算任务开发新的想法;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,该资源将由一个大型计算平台、一组用于系统发育分析的可互操作的高性能软件、一个包含真实的和模拟的数据集及其分析的大型数据库组成;开发人员、研究人员和教育工作者可以通过任何Web浏览器访问该资源。该软件以源代码形式免费提供,将可用于从笔记本电脑到高性能、支持网格的计算引擎(如本项目的平台)的各种规模,并将打包以与当前流行的工具兼容。为了建立这一资源,这一合作项目将支持信息学的研究计划(数据库用于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),优化算法,贝叶斯推理和用于遗传重建的符号操作,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上下文中。生物学,特别是遗传学,在数据采集和分析方面几乎完全被现代信息技术重新定义。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。因此,现在正是生物学家和计算机科学家密切合作解决遗传学中的IT问题的时候,由于组合困难和整体规模的结合,其中许多问题需要新的方法。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,具有成功合作的历史和基础贡献的记录,提供所需的广度和深度。该项目将汇集来自许多领域的研究人员,并培养新型合作和新风格此外,算法、数据库、建模和生物学的相互作用将为每个领域提供新的动力和新的方向。 它将有助于创建研究界将在未来几十年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推断生命之树。该项目将帮助进化生物学家了解进化的机制,生物分子的进化,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,制药学,法医学和安全方面的重大进展。该项目将通过合作机构博物馆合作伙伴的非正式教育项目宣传进化、基因组学和生物信息学。它还将激励高中生和大学生追求生物信息学的职业。该项目提供了一个非凡的机会,培养学生,本科生和研究生,以及博士后研究人员,在科学中最令人兴奋的跨学科领域之一。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。
英文摘要
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.
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