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通过质量控制获得可重复且可靠的微阵列结果:良好的实验室操作水平和恰当的数据分析方法至关重要。

Reproducible and reliable microarray results through quality control: good laboratory proficiency and appropriate data analysis practices are essential.

作者信息

Shi Leming, Perkins Roger G, Fang Hong, Tong Weida

机构信息

National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCRT Road, Jefferson, AR 72079, USA.

出版信息

Curr Opin Biotechnol. 2008 Feb;19(1):10-8. doi: 10.1016/j.copbio.2007.11.003. Epub 2007 Dec 26.

Abstract

Over a few short years, microarray gene expression profiling has permeated most areas of biomedical research. Microarrays are now poised to enter the more demanding realm of clinical applications. The prospect of using microarray data to derive biomarkers of disease or toxicity, predict prognosis, or select treatments raises the validity and reliability bar substantially higher. The potential future payoffs are huge in terms of faster approval of more efficacious and safer medical interventions, and a more personalized implementation of them. Arriving at the future sooner rather than later is the motivation for the FDA-led MicroArray Quality Control (MAQC) project. The widespread collaboration aims to assess achievable technical performance of microarrays and capabilities and limitations of methods for microarray data analysis.

摘要

在短短几年间,微阵列基因表达谱分析已渗透到生物医学研究的大部分领域。如今,微阵列正准备进入要求更高的临床应用领域。利用微阵列数据来推导疾病或毒性的生物标志物、预测预后或选择治疗方法,这一前景大大提高了有效性和可靠性的标准。从更快批准更有效、更安全的医学干预措施以及更个性化地实施这些措施的角度来看,未来潜在的回报是巨大的。尽早而非推迟实现这一未来,是由美国食品药品监督管理局(FDA)牵头的微阵列质量控制(MAQC)项目的动力所在。广泛的合作旨在评估微阵列可实现的技术性能以及微阵列数据分析方法的能力和局限性。

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