Transcription factor binding to the regulatory region of a gene induces or represses its gene expression. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins. These proteins form complexes which bind to the DNA as one-units. The binding of two factors to a shared site does not always lead to a functional interaction. We propose a method to predict the combined functions of two factors using comparable binding and expression data (target). We based this method on binding and expression target analysis (BETA), which we re-implemented in R and extended for this purpose. target ranks the factor’s targets by importance and predicts the dominant type of interaction between two transcription factors. We applied the method to simulated and real datasets of transcription factor-binding sites and gene expression under perturbation of factors. We found that Yin Yang 1 transcription factor (YY1) and YY2 have antagonistic and independent regulatory targets in HeLa cells, but they may cooperate on a few shared targets. We developed an R package and a web application to integrate binding (ChIP-seq) and expression (microarrays or RNA-seq) data to determine the cooperative or competitive combined function of two transcription factors.

中文翻译：

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整合结合和表达数据以预测转录因子的组合功能。

转录因子与基因调控区域的结合诱导或抑制其基因表达。转录因子与其他因子，辅助因子和/或DNA结合蛋白共享其结合位点。这些蛋白质形成复合物，该复合物以一个单位与DNA结合。将两个因素绑定到共享站点并不总是导致功能交互。我们提出了一种方法，使用可比较的结合和表达数据（靶标）预测两个因子的组合功能。我们基于绑定和表达目标分析（BETA）来使用此方法，我们在R中重新实现了该方法并为此进行了扩展。目标按重要性对因子的靶标进行排序，并预测两个转录因子之间相互作用的主要类型。我们将该方法应用于转录因子结合位点和因子干扰下基因表达的模拟和真实数据集。我们发现阴阳1转录因子（YY1）和YY2在HeLa细胞中具有拮抗和独立的调控靶标，但它们可能在一些共享靶标上协同作用。我们开发了一个R程序包和一个Web应用程序来集成绑定（ChIP-seq）和表达（微阵列或RNA-seq）数据，以确定两个转录因子的协同或竞争结合功能。