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A framework for integrative analysis of transcriptional and post-transcriptional gene regulation

机译:转录和转录后基因调控的综合分析框架

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Gene regulation is a complex biological phenomenon. A reliable analysis of this process requires the integration of several data sources in a rigorous pipeline. Here, we propose an approach for simultaneous modeling of transcriptional and post-transcriptional gene regulation over a Bayesian module network. The framework uses paired samples of mRNA and microRNA expressions and their sequence data to produce low-level regulatory circuits in addition to the co-regulated entities of mRNAs, microRNAs and transcription factors. The experiments performed on a real cancer dataset reveal that several biologically meaningful clusters and motifs can be inferred. The results lead to the generation of some testable biological hypotheses.
机译:基因调控是一种复杂的生物学现象。要对该过程进行可靠的分析,需要在严格的管道中集成多个数据源。在这里,我们提出了一种通过贝叶斯模块网络同时建模转录和转录后基因调控的方法。该框架使用成对的mRNA和microRNA表达样本以及它们的序列数据来产生低水平的调控电路,以及mRNA,microRNA和转录因子的共同调控实体。在真实癌症数据集上进行的实验表明,可以推断出几个生物学上有意义的簇和基序。结果导致了一些可检验的生物学假设的产生。

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