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A Statistical Method for Finding Transcription factor Binding Sites

机译:寻找转录因子结合位点的统计方法

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Understanding the mechanisms that determine the regulation of gene expression is an important and challenging problem. A fundamental subproblem is to identify DNA-binding sites for unknown regulatory factors, given a collection of genes believed to be coregulated, and given the noncoding DNA sequences near those genes. We present an enumerative statistical method for identifying good candidates for such transcription factor binding sites. Unlike local search techniques such as Expectation Maximization and Gibbs samplers that may not reach a global optimum, the method proposed here is guaranteed to produce the motifs with greatest z-scores. We discuss the results of experiments in which this algorithm was used to locate candidate binding sites in several well studied pathways of S. cerevisiae, as well as gene clusters from some of the hybridization microarray experiments.
机译:了解确定基因表达调节的机制是一个重要且挑战性的问题。基本亚数标数是鉴定用于未知的调节因素的DNA结合位点,给予被认为是核心的集合,并给予那些基因附近的非分量DNA序列。我们提出了一种统计统计方法,用于鉴定这种转录因子结合位点的良好候选。与本地搜索技术不同,例如可能无法达到全球最佳的预期最大化和GIBBS采样器,所提出的方法是保证具有最大Z分数的图案。我们讨论实验的结果,其中该算法用于在几次杂交微阵列实验中定位几次良好研究的次良好研究途径中的候选粘合位点,以及来自一些杂交微阵列实验的基因簇。

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