KNOWLEDGE BASED BIOLOGICAL MODELING INFORMATION SYSTEM

描述（摘自申请摘要）：基因表达 随着开发的复杂性， 和分化，以及正常与疾病状态的研究， 更多细节 大量的序列数据现在可用于 基因表达研究，沿着预期的高通量 差异基因表达的数据。 许多关键信息仍然存在 在原始文献中无法进行计算分析。 目标 建议项目的目的是在一个单一的综合系统中， 信息管理、分析和可视化工具，其中包含 数据源 这样的系统需要基因表达的表示 包括空间、时间和数量方面; 以及对来自在线资源和主要 文献;为研究量身定制的分析方法的整合 基因表达;以及能够查询和 以人类可理解的形式可视化数据。 原型系统， EpoDB主要关注红细胞生成，但也将推广到基因的研究 沿着任何分化途径表达。 这项研究将提高 并通过以下方式扩展现有的信息管理技术 将声明性约束语言集成到表示中 语言，开发完整性约束系统，以促进 与外部数据库的同步，以及查询的实现 语言和优化器。 模式和受控词汇表将 定制来代表与基因相关的DNA和染色体特征， 调控，描述发育期间表达水平的时间事件 和分化，并描述基因控制过程，途径 和网络。 EpoDB的基础将从网上提取 资源（GenBank，TRANSFAC，MedLine等），重组和分析， 删除错误。 与红细胞生成过程中基因表达相关的数据将 由受过训练的注释者从文献中输入。 的改进版本 将开发数据输入编辑工具，以改进质量控制， 并允许外部用户通过Web进行注释 接口。 数据分析结果也将纳入EpoDB 例如统计发现的转录调节模式 技术、模式匹配技术和分类 基因和模式的层次结构。 EpoDB将通过查询访问 界面和可视化工具，为WWW使用不断发展的 bioTk系统。 数据和系统工具将定期分发 基础

DESCRIPTION (Taken from the application abstract): Gene expression databases will take on growing importance as the complexities of development and differentiation, and normal versus diseased states are studied in greater detail. Vast amounts of sequence data are now available for the study of gene expression, along with an anticipated surge in high-throughput data on differential gene expression. Much of the key information remains in the primary literature inaccessible for computational analysis. The goal of the proposed project is to provide in a single integrated system, the information management, analysis, and visualization tools containing these data sources. Such a system requires the representation of gene expression encompassing spatial, temporal and quantitative dimensions; the collection and encoding of information from online resources and the primary literature; the integration of analysis methodologies tailored to the study of gene expression; and the availability of interfaces able to query and visualize the data in human comprehensible form. The prototype system, EpoDB, focuses on erythropoiesis, but will generalize to the study of gene expression along any pathway of differentiation. This research will enhance and extend the existing information management technology through integration of a declarative constraint language into the representation language, development of an integrity constraint system to facilitate synchronization with external databases, and implementation of a query language and optimizer. Schemas and controlled vocabularies will be tailored to represent DNA and chromosomal features relating to gene regulation, temporal events describing expression levels during development and differentiation, and descriptions of gene control processes, pathways and networks. The foundation for EpoDB will be extracted from online resources (GenBank, TRANSFAC, MedLine, etc.), restructured and analyzed to remove errors. Data relevant to gene expression during erythropoiesis will be entered from the literature by trained annotators. Improved versions of data entry editing tools will be developed to improve quality control, ease of annotation, and allow annotation by external users through Web interfaces. Incorporated into EpoDB will also be results of data analysis such as transcriptional regulatory patterns discovered by statistical techniques, by pattern matching techniques, and by classification hierarchies of genes and patterns. EpoDB will be accessible through query interfaces and visualization tools built for the WWW using the evolving bioTk system. Data and the system tools will be distributed on a regular basis.