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

基本信息

  • 批准号:
    1062565
  • 负责人:
  • 金额:
    $ 140.92万
  • 依托单位:
  • 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

项目摘要

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).
加利福尼亚大学圣地亚哥分校获得了一项赠款,以创建开普勒科学工作流系统(http://kepler-project.org)模块,该模块有助于开发开普勒工作流程,以集成分布式环境中生物知识应用程序的集成执行。下一代DNA测序产生了大量的序列数据,这些数据可用于解决许多科学挑战的许多应用中。 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上进行更高级别的抽象。为了开发这样的环境,生物kikepler项目将创建科学工作流程组件,以使用分布式执行模式执行一组生物信息学工具。定制后,这些科学工作流程将在多个分布式平台上执行,包括各种云和网格计算平台。最初的生物信息学工具将根据各种社区工具和工作流程的评估和集成,以满足研究人员的各种需求,分为八组,涵盖生物信息学应用程序的大多数方面:1)序列数据库搜索; 2)映射; 3)序列组件; 4)基因预测; 5)聚类; 6)多个序列比对,系统发育和分类学; 7)蛋白质注释; 8)其他其他实用程序,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如何影响或改善分布式环境中的工作流程计划和执行。此外,该项目将提供包括开普勒引擎和所有生物依据组件的虚拟机,用于生物信息学工具和应用程序。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。计划中的教育和推广工作的中心原理是培训下一代科学家的重要性。该基本原理还符合该项目的主要目标,以提供工具,以进一步弥合生物信息学和技术之间的差距。这种方法的影响是多重的,包括促进生物信息学家(以及来自其他学科的潜在科学家)使用特定于域特异性的分布式执行组件进行有效,全面和并行的分析,而无需编写一系列代码。除了项目研讨会外,将通过调查进行跟进电话讨论来征求使用方案,而在主要领域会议上的代表性将征求优先级的投入,并提高以后几年对产品的认识。 Biokepler团队致力于多样性,这是由三名女性(包括Pi Altintas)参与七个资助人员组成的,以及包括代表性不足的学生所做的广泛努力。 Biokepler ABI开发项目生产的所有资源,材料和开源软件产品将与摄像机(http://camera.calit2.net/)项目集成,为全球75个国家/地区的近4000个专用用户组成的社区,并将通过Kepler Project网站公开向大型受众访问(HTTP:http:http:kkeer)。

项目成果

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Ilkay Altintas其他文献

Ilkay Altintas的其他文献

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{{ truncateString('Ilkay Altintas', 18)}}的其他基金

Student and Early Career Support: 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023)
学生和早期职业支持:第 23 届 IEEE/ACM 国际集群、云和互联网计算研讨会 (CCGrid 2023)
  • 批准号:
    2317547
  • 财政年份:
    2023
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant
National Data Platform Pilot: Services for Equitable Open Access to Data
国家数据平台试点:公平开放数据访问服务
  • 批准号:
    2333609
  • 财政年份:
    2023
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Continuing Grant
Planning: FIRE-PLAN: Community Building Toward an Immersive Forest Network to Catalyze Wildland Fire Solutions and Training
规划:FIRE-PLAN:建立沉浸式森林网络的社区,以促进荒地火灾解决方案和培训
  • 批准号:
    2341120
  • 财政年份:
    2023
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: FOUNT: Scaffolded, Hands-On Learning for a Data-Centric Future
协作研究:网络培训:实施:媒介:FOUNT:支架式实践学习,打造以数据为中心的未来
  • 批准号:
    2230081
  • 财政年份:
    2022
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant
NSF Convergence Accelerator – Track D: Artificial Intelligence and Community Driven Wildland Fire Innovation via a WIFIRE Commons Infrastructure for Data and Model Sharing
NSF 融合加速器 — 轨道 D:通过 WIFIRE 共享基础设施实现数据和模型共享,人工智能和社区驱动的野地火灾创新
  • 批准号:
    2134904
  • 财政年份:
    2021
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Cooperative Agreement
NSF Convergence Accelerator Track D: Artificial Intelligence and Community Driven Wildland Fire Innovation via a WIFIRE Commons Infrastructure for Data and Model Sharing
NSF 融合加速器轨道 D:通过 WIFIRE 共享基础设施实现数据和模型共享,人工智能和社区驱动的野地火灾创新
  • 批准号:
    2040676
  • 财政年份:
    2020
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant
Collaborative Research: Framework: Software: NSCI : Computational and Data Innovation Implementing a National Community Hydrologic Modeling Framework for Scientific Discovery
合作研究:框架:软件:NSCI:计算和数据创新实施国家社区水文建模框架以促进科学发现
  • 批准号:
    1835855
  • 财政年份:
    2018
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant
Hazards SEES Type 2: WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires
Hazards SEES 类型 2:WIFIRE:可扩展的数据驱动型野火监控、动态预测和弹性网络基础设施
  • 批准号:
    1331615
  • 财政年份:
    2013
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Continuing Grant
EAGER: Interoperability Testbed - Assessing a Layered Architecture for Integration of Existing Capabilities
EAGER:互操作性测试台 - 评估用于集成现有功能的分层架构
  • 批准号:
    1239623
  • 财政年份:
    2012
  • 资助金额:
    $ 140.92万
  • 项目类别:
    Standard Grant

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