Wong Wendy S W, Nielsen Rasmus
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.
Bioinformatics. 2007 Aug 15;23(16):2031-7. doi: 10.1093/bioinformatics/btm299. Epub 2007 Jun 5.
Finding the regulatory modules for transcription factors binding is an important step in elucidating the complex molecular mechanisms underlying regulation of gene expression. There are numerous methods available for solving this problem, however, very few of them take advantage of the increasing availability of comparative genomic data.
We develop a method for finding regulatory modules in Eukaryotic species using phylogenetic data. Using computer simulations and analysis of real data, we show that the use of phylogenetic hidden Markov model can lead to an increase in accuracy of prediction over methods that do not take advantage of the data from multiple species.
The new method is made accessible under GPL in a new publicly available JAVA program: EvoPromoter. It can be downloaded at http://sourceforge.net/projects/evopromoter/.
寻找转录因子结合的调控模块是阐明基因表达调控复杂分子机制的重要一步。有许多方法可用于解决这个问题，然而，其中很少有方法利用日益增多的比较基因组数据。
我们开发了一种利用系统发育数据在真核生物物种中寻找调控模块的方法。通过计算机模拟和对真实数据的分析，我们表明，与未利用多个物种数据的方法相比，使用系统发育隐马尔可夫模型可提高预测准确性。
新方法在GPL许可下通过一个新的公开可用的JAVA程序EvoPromoter提供。可从http://sourceforge.net/projects/evopromoter/下载。
