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Interaction among the gene products contributes to the regulation of gene expression

机译:基因产物之间的相互作用有助于基因表达的调节

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Owing to its complexity, the mechanism of gene regulation for the whole genome is not easily probed with the conventional gene-level analysis. Models of gene regulatory networks (GRN) that are based on a course-grained view of gene regulation, where genes with similar expression profile are grouped in clusters, can aid the inference of important correlations between genes. We propose a model of gene regulation which incorporates the effects of interaction among gene products on the transcription rates. We introduce for that purpose a non-constant rate of gene product degradation which depends on the concentrations of other gene products. Guided by previous reports on the sparseness of GRNs we employ a method of parameter reduction based on interpolating polynomials. We test our model on DNA microarray time series data of Escherichia coli during a glucose-lactose diauxie and report good agreement between data and theory. Our analysis shows that on going from glucose to lactose phase the system becomes highly connected and becomes again sparsely connected in the lactose phase. Out of the many compatible GRNs that our model predicts we chose the ones that satisfy criteria based on robustness, behavior near a fixed point, and fit of the data.
机译:由于其复杂性,通过常规基因水平分析,不容易探测全基因组的基因调节机制。基于基因调控课程视图的基因调节网络(GRN)的模型,其中具有类似表达谱的基因在簇中被分组,可以有助于推理基因之间的重要相关性。我们提出了一种基因调节模型,其含有基因产物对转录率的相互作用的影响。我们为此目的介绍了非恒定率的基因产物降解,这取决于其他基因产物的浓度。以前关于GRN的稀疏的报告指导我们采用基于内插多项式的参数减少方法。我们在葡萄糖乳糖依佐期间测试我们的DNA微阵列时间序列数据的模型,并在数据和理论之间报告良好的一致性。我们的分析表明,在从葡萄糖到乳糖期的情况下,系统变得高度连接,并在乳糖相中再次稀疏地连接。除了许多兼容的GRNS中,我们的模型预测我们选择基于鲁棒性,行为附近的鲁棒性,以及数据的适应性来选择满足标准的那些。

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