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Dynamic Identification and Visualization of Gene Regulatory Networks from Time-Series Gene Expression Profiles

机译:从时间序列基因表达谱动态识别和可视化基因调控网络

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Recent improvements in high-throughput proteomics technology have produced a large amount of time-series gene expression data. The data provide a good resource to uncover causal gene-gene or gene-phenotype relationships and to characterize the dynamic properties of the underlying molecular networks for various biological processes. Several methods have been developed for identifying the molecular mechanisms of regulation of genes from the data, but many of the methods consider static gene expression profiles only. This paper presents a new method for identifying gene regulations from the time-series gene expression data and for visualizing the gene regulations as dynamic gene regulatory networks. The method has been implemented as a program called DRN Builder and successfully tested on actual gene expression profiles. DRN Builder will be useful for generating potential gene regulatory networks from a large amount of time-series gene expression data and for analyzing the identified networks.
机译:高通量蛋白质组学技术的最新改进已产生了大量时序基因表达数据。数据为揭示因果基因与基因或基因表型的关系,以及为各种生物学过程表征潜在分子网络的动态特性提供了很好的资源。已经开发了几种方法来从数据中鉴定调节基因的分子机制,但是许多方法仅考虑静态基因表达谱。本文提出了一种从时间序列基因表达数据中鉴定基因调控并将该基因调控可视化为动态基因调控网络的新方法。该方法已被实现为称为DRN Builder的程序,并已在实际基因表达谱上成功进行了测试。 DRN Builder将有助于从大量时序基因表达数据中生成潜在的基因调控网络,并用于分析已识别的网络。

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