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Managing and querying gene expression data using Curray

机译:使用Curray管理和查询基因表达数据

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Background In principle, gene expression data can be viewed as providing just the three-valued expression profiles of target biological elements relative to an experiment at hand. Although complicated, gathering expression profiles does not pose much of a challenge from a query language standpoint. What is interesting is how these expression profiles are used to tease out information from the vast array of information repositories that ascribe meaning to the expression profiles. Since such annotations are inherently experiment specific functions, much the same way as queries in databases, developing a querying system for gene expression data appears to be pointless. Instead, developing tools and techniques to support individual assignment has been considered prudent in contemporary research. Results We propose a gene expression data management and querying system that is able to support pre-expression, expression and post-expression level analysis and reduce impedance mismatch between analysis systems. To this end, we propose a new, platform-independent and general purpose query language called Curray , for Cu stom Microa rray query language, to support online expression data analysis using distributed resources. It includes features to design expression analysis pipelines using language constructs at the conceptual level. The ability to include user defined functions as a first-class language feature facilitates unlimited analysis support and removes language limitations. We show that Curray’s declarative and extensible features nimbly allow flexible modeling and room for customization. Conclusions The developments proposed in this article allow users to view their expression data from a conceptual standpoint - experiments, probes, expressions, mapping, etc. at multiple levels of representation and independent of the underlying chip technologies. It also allows transparent roll-up and drill-down along representation hierarchies from raw data to standards such as MIAME and MAGE -ML using linguistic constructs. Curray also allows seamless integration with distributed web resources through its LifeDB system of which it is a part.
机译:背景技术原则上,基因表达数据可被视为仅提供相对于手头实验的目标生物元素的三值表达谱。尽管很复杂,但从查询语言的角度来看,收集表达式概要文件并不构成太大的挑战。有趣的是,如何使用这些表达配置文件从大量信息存储库中挑出信息,这些信息存储库赋予表达配置文件以含义。由于此类注释本质上是实验特定的功能,与数据库查询的方式几乎相同,因此开发用于基因表达数据的查询系统似乎毫无意义。相反,在当代研究中,开发支持个人任务的工具和技术被认为是审慎的。结果我们提出了一种基因表达数据管理和查询系统,该系统能够支持表达前,表达和表达后水平的分析,并减少分析系统之间的阻抗不匹配。为此,我们为Cu stom Microa rray查询语言提出了一种新的,独立于平台的通用查询语言,称为Curray,以支持使用分布式资源进行在线表达数据分析。它包括在概念级别使用语言构造来设计表达分析管道的功能。将用户定义的函数作为一流的语言功能包括在内的功能可促进无限的分析支持并消除语言限制。我们证明了Curray的声明性和可扩展功能灵活地提供了灵活的建模和自定义空间。结论本文提出的开发成果使用户可以从概念的角度查看其表达数据-实验,探针,表达,作图等,具有多种表示形式,并且与底层芯片技术无关。它还允许使用语言结构沿从原始数据到标准(例如MIAME和MAGE -ML)的表示层次结构进行透明的上滚和下钻。 Curray还允许通过LifeDB系统与分布式Web资源进行无缝集成,而LifeDB系统是其中的一部分。

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