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Prediction of over Represented Transcription Factor Binding Sites in Co-regulated Genes Using Whole Genome Matching Statistics

机译:使用全基因组匹配统计预测共调节基因的代表转录因子结合位点的预测

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The identification of binding sites for transcription factors regulating gene transcription is one of the most important and challenging problems in molecular biology and bioinformatics. Here we present an algorithm that, given a set of promoters from co-regulated genes, identifies over-represented binding sites by using profiles (position specific frequency matrices) defining the sequence binding specificity of known TFs as well as matching statistics on a whole-genome level, bypassing the need of defining matching thresholds and/or the use of homologous sequences. Preliminary tests performed on experimentally validated sequence sets are very promising; moreover, the same algorithm is suitable also for the use with any model of the binding specificity of TFs.
机译:调节基因转录的转录因子结合位点是分子生物学和生物信息学中最重要和最具挑战性问题之一。在这里,我们提出了一种算法,给定来自共调节基因的一组启动子,通过使用定义已知TFS的序列结合特异性的曲线(位置特异性频率矩阵)来识别过置的结合位点以及整体上的匹配统计数据基因组水平,绕过需要定义匹配阈值和/或使用同源序列。在实验验证的序列集上进行的初步测试非常有前途;此外,相同的算法也适用于与TFS的结合特异性的任何模型一起使用。

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