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首页> 外文期刊>The Indian Journal of Agricultural Sciences >A computational system biology approach to construct gene regulatory networks for salinity response in rice (Oryza sativa)
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A computational system biology approach to construct gene regulatory networks for salinity response in rice (Oryza sativa)

机译:构建水稻盐度响应基因调控网络的计算机系统生物学方法

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摘要

Salinity is one of the most common abiotic stress which limits agricultural crop production. Salinity stress tolerance in rice (Oryza sativa L.) is an important trait controlled by various genes. The mechanism of salinity stress response in rice is quite complex. Modelling and construction of genetic regulatory networks is an important tool and can be used for understanding this underlying mechanism. This paper considers the problem of modeling and construction of Gene Regulatory Networks using Multiple Linear Regression and Singular Value Decomposition approach coupled with a number of computational tools. The gene networks constructed by using this approach satisfied the scale free property of biological networks and such networks can be used to extract valuable information on the transcription factors, which are salt responsive. The gene ontology enrichment analysis of selected nodes is performed. The developed model can also be used for predicting the gene responses under stress condition and the result shows that the model fits well for the given gene expression data in rice. In this paper, we have identified ten target genes and a series of potential transcription factors for each target gene in rice which are highly salt responsive.
机译:盐分是限制农作物产量的最常见的非生物胁迫之一。水稻(Oryza sativa L.)的盐胁迫耐受性是受各种基因控制的重要性状。水稻盐分胁迫响应的机制非常复杂。遗传调控网络的建模和构建是重要的工具,可用于理解这种潜在机制。本文考虑了使用多重线性回归和奇异值分解方法以及许多计算工具对基因调控网络进行建模和构建的问题。通过使用这种方法构建的基因网络满足了生物网络的无标度特性,并且此类网络可用于提取有关盐响应的转录因子的有价值的信息。进行所选节点的基因本体富集分析。所开发的模型还可以用于预测胁迫条件下的基因响应,结果表明该模型非常适合给定的水稻基因表达数据。在本文中,我们已经鉴定了十个目标基因和水稻中每个目标基因的一系列潜在转录因子,它们具有高度的盐响应性。

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