Towards standards for data exchange and integration and their impact on a public database such as CEBS (Chemical Effects in Biological Systems)
Towards standards for data exchange and integration and their impact on a public database such as CEBS (Chemical Effects in Biological Systems)
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DOI：
10.1016/j.taap.2008.06.015
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发表时间：
2008-11-15
影响因子：
3.8
通讯作者：
Fostel, Jennifer M.
中科院分区：
文献类型：
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作者：
Fostel, Jennifer M.
整合，重复使用和荟萃分析的高内容的研究数据，典型的DNA微阵列研究，可以增加其科学效用。获得研究数据和设计参数将加强对各项研究综合数据的挖掘。然而，由于没有交换数据的标准和共同的交换格式，高内容数据的发布非常耗时，而且往往令人望而却步。MGED协会（www.mged.org）的成立是为了响应微阵列数据的广泛出版，以及对数据重用用于荟萃分析的效用的认识。NIEHS开发了生物系统中的化学效应（CEBS）数据库，该数据库可以管理和整合生物和生物医学研究的研究数据和设计。随着研究数据和元数据的社区标准的制定，在CEBS中发布高内容数据将变得越来越简单，这些数据将可用于元分析。正在开发不同的研究数据交换格式：非临床数据交换标准（SEND; www.cdisc.org）;Tox-ML（www.Leadscope.com）和来自NIEHS的简单调查摘要文本（SIFT）。数据集成可以在关于响应基因和表型的结论水平上完成，并且该工作流程由CEBS支持。CEBS还将原始数据和预处理数据集成到给定的平台中。在使用Iconix Pharmaceuticals保存在CEBS中的DrugMatrix数据的示例分析中显示了用于在DNA微阵列研究内和跨DNA微阵列研究整合数据的实用性和方法。(C)2008年爱思唯尔公司All rights reserved.
Integration, re-use and meta-analysis of high content study data, typical of DNA microarray studies, can increase its scientific utility. Access to study data and design parameters would enhance the mining of data integrated across studies. However, without standards for which data to include in exchange, and common exchange formats, publication of high content data is time-consuming and often prohibitive. The MGED Society (www.mged.org) was formed in response to the widespread publication of microarray data, and the recognition of the utility of data re-use for meta-analysis. The NIEHS has developed the Chemical Effects in Biological Systems (CEBS) database, which can manage and integrate study data and design from biological and biomedical studies. As community standards are developed for study data and metadata it will become increasingly straightforward to publish high content data in CEBS, where they will be available for meta-analysis. Different exchange formats for study data are being developed: Standard for Exchange of Nonclinical Data (SEND; www.cdisc.org);Tox-ML (www.Leadscope.com) and Simple Investigation Formatted Text (SIFT) from the NIEHS. Data integration can be done at the level of conclusions about responsive genes and phenotypes, and this workflow is supported by CEBS. CEBS also integrates raw and preprocessed data within a given platform. The utility and a method for integrating data within and across DNA microarray studies is shown in an example analysis using DrugMatrix data deposited in CEBS by Iconix Pharmaceuticals. (C) 2008 Elsevier Inc. All rights reserved.