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Dynamic Complexity of the Temporal Transcriptional Regulation Program in Human Endotoxemia

机译:人类内毒素血症的时间转录调控程序的动态复杂性。

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Human endotoxemia is a well-accepted surrogate model for studying the acute inflammatory responses. In order to discover the complex underlying dynamics, identifying biologically relevant transcriptional regulators as well as their putative regulatory interactions with target genes is an essential step. However, prediction of relevant transcriptional regulators in higher eukaryotes remains a challenge both in silico and in vivo. In this study, we analyzed gene expression data from human blood leukocytes to extract four significant patterns of highly coexpressed genes that capture the essence of inflammatory phases. Upon identification of these patterns, a number of inflammation-specific pathways are selected by evaluating the enrichment of the corresponding subsets. Subsequently, statistically significant cis-regulatory modules (CRMs) are selected and decomposed into a list of relevant transcription factors (34 TFs) which are further validated from prior experiments and computational studies in literature. Additionally, our analysis also allows for the construction of a putative dynamic representation of the transcriptional regulatory program, making it become a critical enabler for unraveling regulatory interactions which is an essential step towards a quantification of dynamic transcriptional regulatory networks.
机译:人类内毒素血症是研究急性炎症反应的公认模型。为了发现复杂的潜在动力学,鉴定生物学上相关的转录调节子以及它们与靶基因的可能的调节相互作用是必不可少的步骤。然而,预测真核生物中相关转录调节子在计算机和体内都仍然是一个挑战。在这项研究中,我们分析了来自人类血液白细胞的基因表达数据,以提取四种高度共表达的基因的重要模式,这些基因捕获了炎症期的实质。一旦确定了这些模式,就可以通过评估相应亚组的富集来选择多种炎症特异性途径。随后,选择具有统计意义的顺式调节模块(CRM),并将其分解为一系列相关转录因子(34 TF),这些转录因子可从先前的实验和文献中的计算研究中进一步验证。此外,我们的分析还允许构建转录调控程序的假定动态表示,使其成为揭示调控相互作用的关键推动力,这是量化动态转录调控网络必不可少的步骤。

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