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A PARALLEL SCHEME FOR COMPARING TRANSCRIPTION FACTOR BINDING SITES MATRICES

机译:用于比较转录因子绑定站点矩阵的并行方案

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Gene regulation implies many mechanisms. Their identification is a crucial task to construct regulatory networks, and is necessary to understand the pathology in many cases. This requires the identification of transcription factors that play a role in regulation. Numerous motif discovery tools are now available. Combining efficiently their results appears useful for comparing and clustering these motifs in order to reduce redundancies and to identify the corresponding transcription factor. We develop a method that produces, compares and clusters a set of motifs and identifies some close motifs in databases like JASPAR and the public version of Transfac. Unlike previous comparison methods, where each matrix column is compared independently, we have developed a global method to compare motifs that also helps to reduce the number of false positives. We also propose an original graph motif model that generalizes the classical position specific pattern matrices. Finally, we present an application of our method to study ChIP-chip data sets in the context of an eukaryotic organism.
机译:基因调控意味着许多机制。对它们的识别是构建监管网络的关键任务,并且在许多情况下是了解病理的必要条件。这需要鉴定在调节中起作用的转录因子。现在有大量的主题发现工具。有效地组合它们的结果对于比较和聚类这些基序以减少冗余并鉴定相应的转录因子似乎是有用的。我们开发了一种方法,该方法可以生成,比较和聚类一组主题,并在JASPAR和Transfac的公共版本等数据库中标识一些接近的主题。与以前的比较方法不同,在以前的比较方法中,每个矩阵列都是独立比较的,我们开发了一种全局方法来比较基元,这也有助于减少假阳性的数量。我们还提出了一个原始的图形主题模型,该模型概括了经典的位置特定的图形矩阵。最后,我们提出了一种在真核生物环境中研究ChIP芯片数据集的方法的应用。

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