基于网络的方法利用推断的转录因子活性来分析遗传变异对基因表达的影响。
Network-based approaches that exploit inferred transcription factor activity to analyze the impact of genetic variation on gene expression.
作者信息
Bussemaker Harmen J, Causton Helen C, Fazlollahi Mina, Lee Eunjee, Muroff Ivor
机构信息
Department of Biological Sciences, Columbia University, New York, NY 10027.
Department of Systems Biology, Columbia University, New York, NY 10032.
出版信息
Curr Opin Syst Biol. 2017 Apr;2:98-102. doi: 10.1016/j.coisb.2017.04.002. Epub 2017 Apr 17.
Abstract
Over the past decade, a number of methods have emerged for inferring protein-level transcription factor activities in individual samples based on prior information about the structure of the gene regulatory network. We discuss how this has enabled new methods for dissecting trans-acting mechanisms that underpin genetic variation in gene expression.
摘要
在过去十年中，基于基因调控网络结构的先验信息，出现了许多用于推断单个样本中蛋白质水平转录因子活性的方法。我们将讨论这如何催生了剖析支撑基因表达遗传变异的反式作用机制的新方法。
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