利用 CAGE 分析转录调控网络

J. Tegnér, J. Björkegren, T. Ravasi, V. Bajic
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引用次数: 0

摘要

绘制一般的细胞网络,特别是转录网络,已被证明是阻碍我们了解生物过程的瓶颈。因此,融合计算和实验技术的综合方法对于高分辨率解码转录网络至关重要。然而,由于真核生物中的基因表达控制是一个复杂的多层次过程,受到多种表观遗传因素的影响,而且调控蛋白与启动子结构之间的相互作用非常微妙,从而对基因表达进行组合调控,因此这一点极具挑战性。在本章中,我们将探讨如何将 CAGE 数据与表达、物理相互作用和调控基团的计算预测等其他测量数据整合在一起,从而在新的分辨率水平上提供真核生物转录调控网络的全基因组图谱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transcription Regulatory Networks Analysis Using CAGE
Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution.
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