Set definition language for relational data
    45.
    发明申请
    Set definition language for relational data 审中-公开
    设置关系数据的定义语言

    公开(公告)号:US20050050030A1

    公开(公告)日:2005-03-03

    申请号:US10895620

    申请日:2004-07-20

    IPC分类号: G06F17/30 G06F17/00

    CPC分类号: G06F16/284

    摘要: The present invention relates to the usage pattern, commonly found in many software applications, of defining sets of objects based on object attributes. A specifically designed set definition language for defining sets, called SDL, is described and a software system that implements this language efficiently on top of a standard relational database management system (RDBMS) is presented. The unique features of the SDL language are the implicit constraints that are enforced on the relational data that belong to the objects. Unique to the SDL system is also the logical metadata of dimensions that enables the SDL system to enforce these constraints across relations. The SDL system utilizes several optimization techniques to enable efficient implementation on top of RDBMS. It is also shown how the SDL language and the SQL language can be merged with bidirectional inlining using syntactic gates. Query composition tools are also described that facilitate the creation of SDL expressions.

    摘要翻译: 本发明涉及许多软件应用中通常发现的基于对象属性定义对象集合的使用模式。 描述了一种用于定义集合的专门设计的集合定义语言,称为SDL,并且提供了在标准关系数据库管理系统(RDBMS)之上有效实现该语言的软件系统。 SDL语言的独特功能是对属于对象的关系数据执行的隐式约束。 SDL系统特有的也是维度的逻辑元数据,使SDL系统能够跨越关系强制实施这些约束。 SDL系统利用多种优化技术,在RDBMS之上实现高效的实现。 还显示了如何使用语法门将SDL语言和SQL语言与双向内联合并。 还描述了查询组合工具,以便于创建SDL表达式。

    Methods for predicting drug sensitivity in patients afflicted with an inflammatory disease

    公开(公告)号:US20030134776A1

    公开(公告)日:2003-07-17

    申请号:US10234652

    申请日:2002-09-03

    发明人: Hakon Hakonarson

    IPC分类号: A61K031/00 C12Q001/68

    摘要: Methods are disclosed for predicting the efficacy of a drug for treating an inflammatory disease in a human patient, including: obtaining a sample of cells from the patient; obtaining a gene expression profile of the sample in the absence and presence of in vitro modulation of the cells with specific cytokines and/or mediators; and comparing the gene expression profile of the sample with a reference gene expression profile, wherein similarities between the sample expression profile and the reference expression profile predicts the efficacy of the drug for treating the inflammatory disease in the patient.