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An interoperable data architecture for data exchange in a biomedical research network

机译:生物医学研究网络中数据交换的可互操作性数据架构

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Knowledge discovery and data correlation require a unified approach to basic data management. However, achieving such an approach is nearly impossible with hundreds of disparate data sources, legacy systems, and data formats. This problem is pervasive in the biomedical research community where data models, taxonomies, and data management systems are locally implemented. These local implementations create an environment where interoperability and collaboration between researchers and research institutions are limited. Investigators from this paper demonstrate how technology developed by NASA's Jet Propulsion Laboratory (JPL) for space science can be used to build an interoperable data architecture for bioinformatics. JPL has taken a novel approach towards solving this problem by exploiting web technologies usually dedicated to e-commerce, combined with a rich, metadata-based environment. This paper discusses the approach taken to develop a prototype data architecture for the discovery and validation of disease biomarkers within a biomedical research network Biomarkers are measured parameters of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers are of growing importance in the biomedical research for therapeutic discovery, disease prevention, and detection. A bioinformatics infrastructure is crucial to support the integration and analysis of large, complex biological and epidemiologic datasets.
机译:知识发现和数据相关需要统一的基本数据管理方法。然而,实现这种方法几乎不可能与数百个不同的数据源,传统系统和数据格式几乎不可能。在本地实施数据模型,分类和数据管理系统的生物医学研究社区中,此问题是普遍存在的。这些本地实现创建了一个环境,其中研究人员和研究机构之间的互操作性和协作是有限的。本文的调查人员展示了NASA的喷气机推进实验室(JPL)开发的技术如何用于空间科学,可用于为生物信息学建立可互操作的数据架构。 JPL通过利用通常致力于电子商务的Web技术进行了一种新的方法来解决这个问题,与富裕的基于元数据的环境相结合。本文讨论了开发原型数据架构的方法,用于发现和验证生物医学研究网络生物标志物的疾病生物标志物是正常生物过程,病原过程或对治疗干预的药理学反应的测量参数。生物标志物在治疗发现,疾病预防和检测的生物医学研究中越来越重要。生物信息学基础设施至关重要,以支持大型,复杂的生物和流行病学数据集的整合和分析。

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