ABI Development: bioKepler: A Comprehensive Bioinformatics Scientific Workflow Module for Distributed Analysis of Large-Scale Biological Data

ABI 开发：bioKepler：用于大规模生物数据分布式分析的综合生物信息学科学工作流程模块

• 批准号: 1062565
• 负责人: Ilkay Altintas
• 金额: $ 140.92万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1062565&HistoricalAwards=false
• 关键词: ABI; Development; bioKepler; Comprehensive; Bioinformatics

The University of California at San Diego is awarded a grant to create a Kepler Scientific Workflow System (http://kepler-project.org) module that facilitates the development of Kepler workflows for integrated execution of bioinformatics applications in distributed environments. Next-generation DNA sequencing generates a very large amount of sequence data that can be used in numerous applications addressing many scientific challenges. This places unprecedented demands on traditional single-processor bioinformatics algorithms. In addition, enabling bioinformaticians and computational biologists to conduct efficient analysis requires higher-level abstractions on top of scientific workflow systems and distributed computing methods. To develop such an environment, the bioKepler project will create scientific workflow components to execute a set of bioinformatics tools using distributed execution patterns. Once customized, these scientific workflow components will be executed on multiple distributed platforms including various Cloud and Grid computing platforms. The initial set of bioinformatics tools will be selected based on an evaluation and integration of a wide range of community tools and workflows to meet the diverse needs of researchers, organized into eight groups covering most aspect of bioinformatics applications: 1) Sequence database searches; 2) Mapping; 3) Sequence assembly; 4) Gene prediction; 5) Clustering; 6) Multiple sequence alignment, phylogeny and taxonomy; 7) Protein annotation; 8) Other miscellaneous utilities including data format transformation and parsing. The project will also study how these distributed execution patterns will affect or improve workflow scheduling and execution in distributed environments. In addition, the project will deliver virtual machines that include a Kepler engine and all the bioKepler components for bioinformatics tools and applications. The developed tools will be applicable to a wide range of bioinformatics and computational biology problems. The central rationale for the planned education and outreach efforts is the importance of training next generation scientists. This rationale also aligns with the primary goal of the project to provide tools to further bridge the gap between bioinformatics and technology. The impact of such an approach is multifold, including facilitating bioinformaticians (and potentially scientists from other disciplines) to conduct efficient, comprehensive and parallelized analyses using domain-specific distributed execution components without writing a single line of code. In addition to the project workshops, usage scenarios will be solicited via surveys with follow-up phone discussions, and representation at major domain conferences will solicit input on priorities and raise awareness of the products in later years. The bioKepler team is committed to diversity as demonstrated by the involvement of three females (including PI Altintas) in the group of seven funded personnel and the broad range of efforts to include underrepresented students. All the resource, materials and the open-source software products produced by the bioKepler ABI Development project will be integrated with the CAMERA (http://camera.calit2.net/) project for a community of nearly 4000 devoted users in over 75 countries worldwide, and will be made publicly available to a larger audience through the Kepler project website (http://kepler-project.org).

加州大学圣地亚哥分校获得了创建开普勒科学工作流系统(http://kepler-project.org)模块)的资助，该模块促进了开普勒工作流的开发，以便在分布式环境中集成执行生物信息学应用程序。下一代DNA测序产生了非常大量的序列数据，这些数据可以用于许多应用程序，解决许多科学挑战。这对传统的单处理器生物信息学算法提出了前所未有的要求。此外，使生物信息学家和计算生物学家能够进行有效的分析，需要在科学工作流系统和分布式计算方法的基础上进行更高级别的抽象。为了开发这样的环境，生物开普勒项目将创建科学的工作流程组件，以使用分布式执行模式执行一组生物信息学工具。一旦定制，这些科学工作流组件将在多个分布式平台上执行，包括各种云和网格计算平台。最初的一套生物信息学工具将在评估和整合各种社区工具和工作流程的基础上选出，以满足研究人员的不同需求，分为八组，涵盖生物信息学应用的大部分方面：1)序列数据库搜索；2)测绘；3)序列组装；4)基因预测；5)聚类；6)多序列比对、系统发育和分类学；7)蛋白质注释；8)其他各种实用工具，包括数据格式转换和解析。该项目还将研究这些分布式执行模式将如何影响或改进分布式环境中的工作流调度和执行。此外，该项目将交付包括开普勒引擎和用于生物信息学工具和应用的所有生物开普勒组件的虚拟机。所开发的工具将适用于广泛的生物信息学和计算生物学问题。计划中的教育和外展工作的主要理由是培训下一代科学家的重要性。这一理论基础也符合该项目的主要目标，即提供进一步弥合生物信息学和技术之间差距的工具。这种方法的影响是多方面的，包括促进生物信息学家(以及可能来自其他学科的科学家)使用特定于领域的分布式执行组件进行高效、全面和并行的分析，而无需编写一行代码。除了项目研讨会外，还将通过调查和后续电话讨论征求使用方案，在主要领域会议上的代表将征求对优先事项的意见，并在以后几年提高对产品的认识。生物开普勒团队致力于多样性，这一点体现在七名受资助人员中有三名女性(包括Pi Altintas)，以及为吸纳代表性不足的学生所作的广泛努力。生物开普勒ABI开发项目生产的所有资源、材料和开源软件产品将与照相机(http://camera.calit2.net/)项目)整合在一起，该项目面向全球75个以上国家和地区的近4,000名忠实用户，并将通过开普勒项目网站(http://kepler-project.org).)向更多的受众公开