Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
J Theor Biol. 2012 Jul 7;304:96-102. doi: 10.1016/j.jtbi.2012.03.039. Epub 2012 Apr 6.
Gene expression is the main cause for the existence of various phenotypes. Through this procedure, the information stored in DNA rises to the phenotype. Essentially, gene expression is dependent upon the successful binding of transcription factors (TFs) - a specific type of proteins - to explicit positions in its upstream, TF binding sites (TFBSs). Unfortunately, finding these TFBSs is costly and laborious; therefore, discovering TFBSs computationally is a significant problem that many researches endeavor to solve. In this paper, a new TFBS discovery method is presented by considering known biological facts about TFBSs. The input to this method includes sequences with arbitrary lengths and the output comprises positions that tend to be TFBS. Through the application of previous methods along with a method that focuses on biological and simulated datasets, it is shown that this method achieves higher accuracy in discovering TFBSs.
基因表达是各种表型存在的主要原因。通过这个过程，储存在 DNA 中的信息上升到表型。从本质上讲，基因表达依赖于转录因子（TFs）——一种特殊类型的蛋白质——成功结合到其上游的特定位置，即转录因子结合位点（TFBSs）。不幸的是，找到这些 TFBSs 既昂贵又费力；因此，计算上发现 TFBSs 是许多研究人员努力解决的一个重要问题。在本文中，提出了一种新的 TFBS 发现方法，该方法考虑了关于 TFBS 的已知生物学事实。该方法的输入包括任意长度的序列，输出包括倾向于成为 TFBS 的位置。通过应用以前的方法以及一种专注于生物和模拟数据集的方法，结果表明该方法在发现 TFBS 方面具有更高的准确性。
