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通过网络动态理解癌症机制。

Understanding cancer mechanisms through network dynamics.

机构信息

Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields, London WC2A 3LY, UK.

出版信息

Brief Funct Genomics. 2012 Nov;11(6):543-60. doi: 10.1093/bfgp/els025. Epub 2012 Jul 18.

Abstract

Cancer is a complex, multifaceted disease. Cellular systems are perturbed both during the onset and development of cancer, and the behavioural change of tumour cells usually involves a broad range of dynamic variations. To an extent, the difficulty of monitoring the systemic change has been alleviated by recent developments in the high-throughput technologies. At both the genomic as well as proteomic levels, the technological advances in microarray and mass spectrometry, in conjunction with computational simulations and the construction of human interactome maps have facilitated the progress of identifying disease-associated genes. On a systems level, computational approaches developed for network analysis are becoming especially useful for providing insights into the mechanism behind tumour development and metastasis. This review emphasizes network approaches that have been developed to study cancer and provides an overview of our current knowledge of protein-protein interaction networks, and how their systemic perturbation can be analysed by two popular network simulation methods: Boolean network and ordinary differential equations.

摘要

癌症是一种复杂的、多方面的疾病。在癌症的发生和发展过程中,细胞系统会受到干扰,而肿瘤细胞的行为变化通常涉及广泛的动态变化。在一定程度上,高通量技术的发展缓解了监测系统变化的难度。在基因组和蛋白质组水平上,微阵列和质谱技术的技术进步,结合计算模拟和人类相互作用图谱的构建,促进了识别疾病相关基因的进展。在系统水平上,为网络分析而开发的计算方法对于深入了解肿瘤发生和转移的机制变得尤其有用。本综述强调了已开发用于研究癌症的网络方法,并概述了我们目前对蛋白质-蛋白质相互作用网络的认识,以及如何通过两种流行的网络模拟方法:布尔网络和常微分方程来分析它们的系统干扰。

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