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Rhodobase, a meta-analytical tool for reconstructing gene regulatory networks in a model photosynthetic bacterium

机译:Rhodobase,一种在模型光合细菌中重建基因调控网络的元分析工具

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摘要

We present Rhodobase, a web-based meta-analytical tool for analysis of transcriptional regulation in a model anoxygenic photosynthetic bacterium, Rhodobacter sphaeroides. The gene association meta-analysis is based on the pooled data from 100 of R. sphaeroides whole-genome DNA microarrays. Gene-centric regulatory networks were visualized using the StarNet approach (Jupiter, D.C., VanBuren, V., 2008. A visual data mining tool that facilitates reconstruction of transcription regulatory networks. PLoS ONE 3, e1717) with several modifications. We developed a means to identify and visualize operons and superoperons. We designed a framework for the cross-genome search for transcription factor binding sites that takes into account high GC-content and oligonucleotide usage profile characteristic of the R. sphaeroides genome. To facilitate reconstruction of directional relationships between co-regulated genes, we screened upstream sequences (-400 to +20 bp from start codons) of all genes for putative binding sites of bacterial transcription factors using a self-optimizing search method developed here. To test performance of the meta-analysis tools and transcription factor site predictions, we reconstructed selected nodes of the R. sphaeroides transcription factor-centric regulatory matrix. The test revealed regulatory relationships that correlate well with the experimentally derived data. The database of transcriptional profile correlations, the network visualization engine and the optimized search engine for transcription factor binding sites analysis are available at http://rhodobase.org.
机译:我们提出了Rhodobase,一种基于网络的荟萃分析工具,用于在模型无氧光合细菌sphaeroides sphaeroides中分析转录调控。基因关联的荟萃分析是基于来自100个球形鳞茎全基因组DNA微阵列的汇总数据。使用星网方法(Jupiter,D.C.,VanBuren,V.,2008.一种可视化数据挖掘工具,可促进转录调控网络的重建,PLoS ONE 3,e1717),以基因为中心,对调控网络进行了可视化。我们开发了一种识别和可视化操纵子和超级操纵子的方法。我们设计了一个跨基因组搜索转录因子结合位点的框架,该框架考虑了球形红球菌基因组的高GC含量和寡核苷酸使用情况。为了促进共调控基因之间方向关系的重建,我们使用在此开发的自优化搜索方法筛选了所有基因的上游序列(起始密码子为-400至+20 bp)以寻找细菌转录因子的假定结合位点。为了测试荟萃分析工具和转录因子位点预测的性能,我们重建了球形红球菌以转录因子为中心的调节矩阵的选定节点。该测试揭示了与实验得出的数据密切相关的调节关系。转录概况相关性数据库,网络可视化引擎和用于转录因子结合位点分析的优化搜索引擎可从http://rhodobase.org获得。

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