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MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes

机译:MAPPER:用于在多个基因组中推定转录因子结合位点的计算鉴定的搜索引擎

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Background Cis -regulatory modules are combinations of regulatory elements occurring in close proximity to each other that control the spatial and temporal expression of genes. The ability to identify them in a genome-wide manner depends on the availability of accurate models and of search methods able to detect putative regulatory elements with enhanced sensitivity and specificity. Results We describe the implementation of a search method for putative transcription factor binding sites (TFBSs) based on hidden Markov models built from alignments of known sites. We built 1,079 models of TFBSs using experimentally determined sequence alignments of sites provided by the TRANSFAC and JASPAR databases and used them to scan sequences of the human, mouse, fly, worm and yeast genomes. In several cases tested the method identified correctly experimentally characterized sites, with better specificity and sensitivity than other similar computational methods. Moreover, a large-scale comparison using synthetic data showed that in the majority of cases our method performed significantly better than a nucleotide weight matrix-based method. Conclusion The search engine, available at http://mapper.chip.org , allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, fly, worm and yeast genomes. In addition it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. Due to its extensive database of models, powerful search engine and flexible interface, MAPPER represents an effective resource for the large-scale computational analysis of transcriptional regulation.
机译:背景顺式调节模块是彼此紧邻的调节元件的组合,其控制基因的空间和时间表达。以全基因组方式鉴定它们的能力取决于准确模型的可用性以及能够以提高的灵敏度和特异性检测假定的调控元件的搜索方法。结果我们描述了基于已知位点比对建立的隐马尔可夫模型的推定转录因子结合位点(TFBS)搜索方法的实现。我们使用实验确定的由TRANSFAC和JASPAR数据库提供的位点序列比对,建立了1,079个TFBS模型,并用它们来扫描人,小鼠,果蝇,蠕虫和酵母基因组的序列。在一些经过测试的情况下,该方法可以正确地鉴定出具有实验特征的位点,比其他类似的计算方法具有更好的特异性和灵敏度。此外,使用合成数据进行的大规模比较表明,在大多数情况下,我们的方法比基于核苷酸重量矩阵的方法执行得更好。结论可以从http://mapper.chip.org获得的搜索引擎可以识别,可视化和选择在人类,小鼠,苍蝇,蠕虫和酵母基因组的基因的启动子或其他区域中出现的假定TFBS。此外,它允许用户上传序列进行查询,并通过提供感兴趣的转录因子的结合位点的多序列比对来构建模型。由于其广泛的模型数据库,强大的搜索引擎和灵活的界面,MAPPER代表了大规模的转录调控计算分析的有效资源。

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