Gitter Anthony, Bar-Joseph Ziv
Microsoft Research, Cambridge, MA, 02142, USA,
Methods Mol Biol. 2016;1303:493-506. doi: 10.1007/978-1-4939-2627-5_30.
The Signaling and Dynamic Regulatory Events Miner (SDREM) is a powerful computational approach for identifying which signaling pathways and transcription factors control the temporal cellular response to a stimulus. SDREM builds end-to-end response models by combining condition-independent protein-protein interactions and transcription factor binding data with two types of condition-specific data: source proteins that detect the stimulus and changes in gene expression over time. Here we describe how to apply SDREM to study human diseases, using epidermal growth factor (EGF) response impacting neurogenesis and Alzheimer's disease as an example.
信号与动态调控事件挖掘器(SDREM)是一种强大的计算方法,用于识别哪些信号通路和转录因子控制细胞对刺激的时间响应。SDREM通过将与条件无关的蛋白质-蛋白质相互作用和转录因子结合数据与两种类型的条件特异性数据相结合,构建端到端的响应模型:检测刺激的源蛋白和基因表达随时间的变化。在这里,我们以影响神经发生和阿尔茨海默病的表皮生长因子(EGF)反应为例,描述如何应用SDREM来研究人类疾病。