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从组学到肾脏病学的个体化医学:整合是关键。

From -omics to personalized medicine in nephrology: integration is the key.

机构信息

Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK.

出版信息

Nephrol Dial Transplant. 2013 Jan;28(1):24-8. doi: 10.1093/ndt/gfs483. Epub 2012 Dec 9.

DOI:10.1093/ndt/gfs483
PMID:23229923
Abstract

Large-scale gene, protein and metabolite measurements ('omics') have driven the resolution of biology to an unprecedented high definition. Passing from reductionism to a system-oriented perspective, medical research will take advantage of these high-throughput technologies unveiling their full potential. Integration is the key to decoding the underlying principles that govern the complex functions of living systems. Extensive computational support and statistical modelling is needed to manage and connect the -omic data sets but this, in turn, is speeding up the hypothesis generation in biology enormously and yielding a deep insight into the pathophysiology. This systems biology approach will transform diagnostic and therapeutic strategies with the discovery of novel biomarkers that will enable a predictive and preventive medicine leading to personalized medicine.

摘要

大规模的基因、蛋白质和代谢物测量(组学)将生物学的分辨率提升到了前所未有的高度。从还原论到系统论的观点转变,医学研究将利用这些高通量技术来充分发挥其潜力。整合是解码控制生命系统复杂功能的基本原理的关键。需要广泛的计算支持和统计建模来管理和连接组学数据集,但这反过来又极大地加速了生物学中的假设生成,并深入了解病理生理学。这种系统生物学方法将通过发现新的生物标志物来改变诊断和治疗策略,从而实现预测性和预防性医学,进而实现个性化医学。

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