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

• 批准号: 0331495
• 负责人: Max Gunzburger
• 金额: --
• 依托单位: Florida State University
• 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 2010-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0331495&HistoricalAwards=false
• 关键词: Information; Technology; Research; ITR; Building

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.

这一合作项目旨在建立一个国家计算资源，使研究界更接近实现生命之树倡议的目标，即重建所有有机体的进化史。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，它们无法在其范围的高端提供足够的精度。计划中的资源将被设计为一个孵化器，以促进这一具有巨大挑战性的计算任务的新想法的发展；它将为实验者、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，同时支持当前的生物学研究项目。资源将由一个大型计算平台、一组可互操作的高性能系统发育分析软件和一个大型数据库组成，其中包括真实和模拟的数据集及其分析；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。该软件以源代码的形式免费提供，将在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)的各种规模上使用，并将打包以与当前流行的工具兼容。为了建立这个资源，这个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)、系统发生重建的优化算法、贝叶斯推理和符号处理以及基因组水平的分支进化模拟等研究项目，所有这些都在虚拟合作中心的背景下进行。生物学，特别是系统发育学，几乎完全被现代信息技术重新定义，无论是在数据获取方面还是在分析方面。系统发育学家已经制定了具体的模型和问题，现在可以利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中的IT问题的时候了，由于组合难度和整体规模的结合，其中许多问题需要新的方法。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，他们有成功合作的历史和基本贡献的记录，以提供所需的广度和深度。该项目将汇集来自多个领域的研究人员，并促进计算生物学的新型合作和新的研究风格；此外，算法、数据库、建模和生物学的相互作用将在每个领域提供新的动力和新的方向。这将有助于建立未来几十年研究界将使用的计算基础设施，因为更多的完整基因组被测序，并收集了足够的数据来尝试推断生命树。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生追求生物信息学的职业生涯。该项目提供了一个非同寻常的机会来培训学生，包括本科生和研究生，以及博士后研究人员，在科学领域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。