Design and Implementation of Effective Solutions for Archiving and Processing Systems Biology Data: Research Integrated with an Ongoing High School Education Program.

归档和处理系统生物学数据的有效解决方案的设计和实施：研究与正在进行的高中教育计划相结合。

• 批准号: 0640950
• 负责人: Nitin Baliga
• 金额: $ 184.53万
• 依托单位: Institute for Systems Biology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2012-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0640950&HistoricalAwards=false
• 关键词: Design; Implementation; Effective; Solutions; Archiving

The Institute of Systems Biology is awarded a grant to design an informatics solution for the integration of systems biology data to expedite network inference and knowledge discovery. Specific aims include (1) definition of a flexible data standard for capturing experiment and sample information in digital form (2) development of tools to assist data curation, retrieval, and statistical analysis; and (3) creation of education -oriented database extensions that facilitate high-school training programs. As part of the project, the PI's will develop an inquiry based education program in systems biology that brings mathematics, natural science and computer science to high-school curricula.The central strategy of the project is motivated by a key observation that, although complex, each data type (for example, microarray ratios, tandem mass spectra, protein/DNA networks, sequences, annotations etc.) is usually well-defined in its 'native' context, and that complexity arises mostly when these data are combined. Tools and approaches developed in this project will, therefore, capitalize on virtues of independent small, specialized and robust databases and software, and enable downstream integration by loosely connecting these sub-systems using carefully crafted rules and technologies such as Java RMI. An important provision of this simple approach will allow researchers to dynamically relate their data to other valuable remotely managed databases through an evolving set of rules, and an inference engine that applies these rules. Furthermore, because experiment design and sample processing are indispensable while analyzing data to draw meaningful insights, data integration will be guided by a flexible experiment meta-information schema, which will be formalized in this project. To extend practicality of this data schema for day-to-day use, user-friendly software tools developed in this project will interface laboratory scientists directly with automated data processing pipelines to help capture experiment details and create this meta-information schema.

系统生物学研究所获得拨款，用于设计信息学解决方案，用于整合系统生物学数据，以加快网络推理和知识发现。具体目标包括（1）定义灵活的数据标准，用于以数字形式捕获实验和样本信息（2）开发辅助数据管理、检索和统计分析的工具； (3) 创建面向教育的数据库扩展，以促进高中培训计划。作为该项目的一部分，PI 将开发一个基于探究的系统生物学教育计划，将数学、自然科学和计算机科学引入高中课程。该项目的中心策略是由一个关键观察推动的，即尽管很复杂，但每种数据类型（例如，微阵列比率、串联质谱、蛋白质/DNA 网络、序列、注释等）通常在其“本地”环境中得到明确定义，并且这种复杂性 主要是在合并这些数据时出现的。因此，该项目中开发的工具和方法将利用独立的小型、专业和强大的数据库和软件的优点，并通过使用精心设计的规则和技术（例如 Java RMI）松散地连接这些子系统来实现下游集成。这种简单方法的一个重要规定将允许研究人员通过一组不断发展的规则以及应用这些规则的推理引擎，动态地将他们的数据与其他有价值的远程管理数据库相关联。此外，由于在分析数据以得出有意义的见解时实验设计和样本处理是必不可少的，因此数据集成将由灵活的实验元信息模式指导，该模式将在该项目中正式化。为了扩展该数据模式的实用性以供日常使用，该项目中开发的用户友好的软件工具将直接将实验室科学家与自动化数据处理管道连接起来，以帮助捕获实验细节并创建此元信息模式。