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从图像推断信号网络。

Inferring signalling networks from images.

机构信息

Chester Beatty Laboratories, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London, UK, SW3 6JB.

出版信息

J Microsc. 2013 Oct;252(1):1-7. doi: 10.1111/jmi.12062. Epub 2013 Jul 11.

Abstract

The mapping of signalling networks is one of biology's most important goals. However, given their size, complexity and dynamic nature, obtaining comprehensive descriptions of these networks has proven extremely challenging. A fast and cost-effective means to infer connectivity between genes on a systems-level is by quantifying the similarity between high-dimensional cellular phenotypes following systematic gene depletion. This review describes the methodology used to map signalling networks using data generated in the context of RNAi screens.

摘要

信号网络的映射是生物学最重要的目标之一。然而,由于它们的规模、复杂性和动态性质,获得这些网络的全面描述已被证明极具挑战性。在系统水平上推断基因之间连通性的快速且具有成本效益的方法是通过量化系统基因耗竭后高维细胞表型之间的相似性。本文综述了使用 RNAi 筛选背景下生成的数据绘制信号网络的方法。

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