SGER GeneBeans: A Modular System That Makes Genomic-Scale Analysis Accessible to Biologists

SGER GeneBeans：使生物学家能够进行基因组规模分析的模块化系统

• 批准号: 0234250
• 负责人: Ann Stapleton
• 金额: $ 9.19万
• 依托单位: University of North Carolina at Wilmington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0234250&HistoricalAwards=false
• 关键词: SGER; GeneBeans; Modular; System; Makes

Biologists now have access to vast amounts of DNA sequence and annotation data, but do not yet have tool sets that make it easy for a novice to ask biological questions about these large sequence data sets. An environment with a visual user interface for constructing series of queries and analyses without the need for the user to see the underlying computer code will be created. The system will use Enterprise JavaBeans (EJBs) to import sequence data from a variety of sources and store it in a relational database. Other EJBs will handle workflow, query the database, and analyze results. The EJB modules will be designed to make their results available to other modules. The system will be extensible in that it will be easy to add new modules that employ the appropriate interfaces. This system will allow users to ask questions about frequency, correlation, and significance, queries typical of data mining methods, without writing new programs. The prototype of our system will be tested both for undergraduate classroom use at a historically black university, NCA&T, and for research on genome structure in plant DNA sequences. New kinds of search algorithms and statistical analyses, which will be easily integrated into our modular system, will be designed involving the interdisciplinary training of a biology graduate student.

现在，生物学家可以访问大量的DNA序列和注释数据，但尚无工具集，使新手可以轻松地提出有关这些大序列数据集的生物学问题。具有可视用户界面的环境，用于构建一系列查询和分析，而无需用户查看基础计算机代码。该系统将使用企业Javabeans（EJB）从各种来源导入序列数据，并将其存储在关系数据库中。其他EJB将处理工作流程，查询数据库并分析结果。 EJB模块将设计为使其结果可用于其他模块。该系统将是可扩展的，因为添加采用适当接口的新模块很容易。该系统将允许用户在不编写新程序的情况下询问有关频率，相关性和意义的问题，即数据挖掘方法的典型查询。我们系统的原型将在历史悠久的黑人大学（NCA＆T）以及植物DNA序列中的基因组结构进行研究。新型的搜索算法和统计分析将很容易集成到我们的模块化系统中，涉及生物学研究生的跨学科培训。