BAYESIAN INFERENCES OF CIS-REGULATORY MODULES AND SIGNAL TRANSDUCTION PATHWAYS

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。所列机构为中心机构，不一定为研究者机构。该项目有两个互补的目标：1）确定性腺特异性启动子调控元件的顺式调控模块;和2）改进用于识别此类模块的统计技术。为此，我们将应用贝叶斯统计推断方法来识别由于TAF 4 b水平变化而直接导致表达水平改变的基因，并且我们将基于吉布斯抽样，使用系统发育模型来增强我们当前的算法。相关物种基因之间的关系。此外，我们将更新的算法与增强模型的网站之间的空间分布;一个改进的方法，用于检测短顺式结合模式;一个更高阶的模型的背景部分的序列数据;和一个方法的基序模型的聚类，以提高收敛性。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project has two complementary goals: 1) the identification of the cis-regulatory modules of gonad specific promoter regulatory elements; and 2) improvements of statistical technology for the identification of such modules. To these ends, we will apply Bayesian statistical inference methods to identify genes whose level of expression are altered as a direct result of changes in the levels of TAF4b and we will enhance our current algorithms, based on Gibbs sampling, with a model of the phylogenetic relationship among genes from related species. In addition, we will update the algorithm with an enhanced model of the spatial distribution among sites; an improved method for detection of short cis-binding patterns; a higher order model for the background portions of sequence data; and a method for the clustering of motif models to improve convergence.