Faculty of Computer Science, Alexandru I. Cuza University, Iasi 700483, Romania Berlin Institute for Medical Systems Biology, Max Delbruck Center, 13125 Berlin, Germany.
Berlin Institute for Medical Systems Biology, Max Delbruck Center, 13125 Berlin, Germany Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27708, USA.
Nucleic Acids Res. 2014 Jul;42(Web Server issue):W461-7. doi: 10.1093/nar/gku435. Epub 2014 May 26.
Most transcription factors (TFs) belong to protein families that share a common DNA binding domain and have very similar DNA binding preferences. However, many paralogous TFs (i.e. members of the same TF family) perform different regulatory functions and interact with different genomic regions in the cell. A potential mechanism for achieving this differential in vivo specificity is through interactions with protein co-factors. Computational tools for studying the genomic binding profiles of paralogous TFs and identifying their putative co-factors are currently lacking. Here, we present an interactive web implementation of COUGER, a classification-based framework for identifying protein co-factors that might provide specificity to paralogous TFs. COUGER takes as input two sets of genomic regions bound by paralogous TFs, and it identifies a small set of putative co-factors that best distinguish the two sets of sequences. To achieve this task, COUGER uses a classification approach, with features that reflect the DNA-binding specificities of the putative co-factors. The identified co-factors are presented in a user-friendly output page, together with information that allows the user to understand and to explore the contributions of individual co-factor features. COUGER can be run as a stand-alone tool or through a web interface: http://couger.oit.duke.edu.
大多数转录因子 (TFs) 属于具有共同 DNA 结合结构域且具有非常相似 DNA 结合偏好的蛋白质家族。然而,许多同源 TF(即同一 TF 家族的成员)执行不同的调控功能,并与细胞中不同的基因组区域相互作用。实现这种体内特异性差异的一个潜在机制是通过与蛋白质共因子相互作用。目前,用于研究同源 TF 的基因组结合谱并识别其潜在共因子的计算工具还很缺乏。在这里,我们提出了一种交互式网络实现 COUGER,这是一种基于分类的框架,用于识别可能为同源 TF 提供特异性的蛋白质共因子。COUGER 将两个由同源 TF 结合的基因组区域作为输入,并确定一小部分最能区分这两个序列集的假定共因子。为了完成这项任务,COUGER 使用分类方法,其特征反映了假定共因子的 DNA 结合特异性。所鉴定的共因子将在用户友好的输出页面中呈现,并提供允许用户理解和探索单个共因子特征贡献的信息。COUGER 可以作为独立工具运行,也可以通过网络界面运行:http://couger.oit.duke.edu。