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The development of a database for metabolomics -looking back on ten years of experience

机译:代谢组学数据库的开发-回顾十年的经验

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摘要

Metabolome profiles of ca. 750 compounds obtained from blood samples from 28 day rat studies (OECD 407) were combined with toxicity profiles in one database over ten years to predict toxicity of new compounds. We provide detailed descriptions of procedures and recommendations for 'omics data-bases. Control of variability (biological, sampling/storage and technical measurement) is essential. At the start of large scaleprojects control variability should be extensively investigated. Reference (positivecontrol) substances should be used to evaluate and obtain a good signaloise ratio. Procedures should be documented in standard operating procedures and followed meticulously. Exact repeats of positive controls should be regularly performed, to assessvariability of positive responses. Control data should be regularly checked for shifts and analysed to obtain information concerningnormality. If possible, data should be analysed by multiple procedures and conclusions should be drawn based on a joint assessment, not unlike peer review processes in histopathology.
机译:ca的代谢组概况。从一项为期28天的大鼠研究(OECD 407)的血液样本中获得的750种化合物与毒性谱图结合在一个数据库中,历时十年,以预测新化合物的毒性。我们提供有关“组学数据库”的程序和建议的详细说明。控制变异性(生物,采样/存储和技术测量)至关重要。在大型项目开始时,应广泛研究控制变异性。应使用参考(阳性对照)物质评估并获得良好的信噪比。程序应记录在标准操作程序中,并严格遵守。应定期进行阳性对照的精确重复,以评估阳性反应的变异性。应定期检查控制数据是否有变化,并进行分析以获得有关正常性的信息。如果可能,应通过多种程序分析数据,并应基于联合评估得出结论,与组织病理学的同行评审过程不同。

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