SEI(BIO)+II: A Collaborative Scientific Workflow Environment for Accelerating Genome-Scale Biological Research

SEI(BIO) II：加速基因组规模生物学研究的协作科学工作流程环境

• 批准号: 0612326
• 负责人: Bertram Ludaescher
• 金额: $ 60.01万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0612326&HistoricalAwards=false
• 关键词: SEI; BIO; +II; Collaborative; Scientific

This project will develop a system that integrates a web-based experiment workspace environment with a flexible scientific workflow automation system supporting rapid prototyping and user-transparent distributed computing. The experiment-workspace web interface will provide biologists an extensible virtual laboratory for defining computational protocols, executing "experiments" based on those protocols, visualizing data in the context of their provenance, and managing projects. The KEPLER scientific workflow system will be extended to automate the enactment of these experiments on available distributed resources and will record workflow and data provenance. Bioinformatics specialists and software engineers will develop new experiment templates using the system and will share these templates with experiment-workspace users. The system will support users who can make effective use of both interfaces and will facilitate productive collaboration between biologists, bioinformatics specialists, and software developers. A prototype of this system will integrate and accelerate computational and experimental components of research projects employing a sequential chromatin immunoprecipitation followed by DNA microarray analysis (ChIP-chip) for identifying direct transcription factor targets. The IT and CS challenges in automating ChIP-chip workflows are typical of those plaguing complex, genome-scale analyses (e.g., dealing with multiple, alternate or related analysis modules simultaneously; managing thousands of workflow runs and resulting datasets; recording workflow, data and parameter dependencies; etc.) Implementing this system will require innovative approaches for managing nested collections of scientific data, combining functional programming and stream-processing methodologies for scientific workflows, and generalizing data-typing and integration approaches for supporting interoperability of workflow components developed by different organizations.This proposal brings together investigators recognized for their expertise in scientific workflow modeling, design, and automation; scientific data management; ChIP-chip research and data analysis; and development of collaborative computational environments for scientific research, which together will enhance student engagement in the research.

该项目将开发一个系统，将基于网络的实验工作空间环境与支持快速原型和用户透明的分布式计算的灵活的科学工作流程自动化系统相结合。实验-工作区网络界面将为生物学家提供一个可扩展的虚拟实验室，用于定义计算协议、基于这些协议执行“实验”、在其出处的背景下可视化数据以及管理项目。开普勒科学工作流程系统将得到扩展，以在现有的分布式资源上自动执行这些实验，并将记录工作流程和数据来源。生物信息学专家和软件工程师将使用该系统开发新的实验模板，并将与实验工作区用户共享这些模板。该系统将支持能够有效利用这两个界面的用户，并将促进生物学家、生物信息学专家和软件开发人员之间的富有成效的合作。该系统的原型将整合和加速使用顺序染色质免疫沉淀和DNA微阵列分析(芯片-芯片)识别直接转录因子靶标的研究项目的计算和实验部分。自动化芯片工作流中的IT和CS挑战是困扰复杂的基因组规模分析的典型问题(例如，同时处理多个、替代的或相关的分析模块；管理数千个工作流运行和结果数据集；记录工作流、数据和参数依赖关系；等等)。实施这一系统将需要创新的方法来管理嵌套的科学数据集合，结合功能编程和科学工作流处理方法，并推广数据类型和集成方法，以支持不同组织开发的工作流组件的互操作性。这项建议将在科学工作流建模、设计和自动化、科学数据管理、芯片研究和数据分析以及开发科学研究的协作计算环境方面公认的研究人员聚集在一起，这将共同加强学生对研究的参与。