DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data.
DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data.
复制标题
DOI：
10.1186/1752-0509-6-104
复制
发表时间：
2012-08-16
影响因子：
--
通讯作者：
Bar-Joseph Z
中科院分区：
文献类型：
--
作者：
Schulz MH;Devanny WE;Gitter A;Zhong S;Ernst J;Bar-Joseph Z
建模动态调控网络是一个重大挑战，因为大部分的蛋白质-DNA相互作用的数据是静态的。动态调控事件挖掘器（DREM）使用基于隐马尔可夫模型的方法将这种静态相互作用数据与时间序列基因表达相结合，从而生成可以确定转录因子（TF）何时激活基因以及它们调节哪些基因的模型。DREM已成功应用于生物学研究的各个领域。然而，有几个问题在最初的版本中没有得到解决。DREM 2.0是一个用于重建动态调控网络的综合软件，支持交互式图形或批处理模式。与2.0版相比，引入了一系列与其他软件相比独特的新功能。首先，我们提供额外物种的静态相互作用数据。其次，DREM 2.0现在接受连续的绑定值，我们添加了一个新的方法来利用TF表达水平时，搜索动态模型。第三，我们增加了对歧视性基序发现的支持，这对于实验相互作用数据有限的物种来说特别强大。最后，我们改进了可视化以支持新功能。结合起来，这些变化提高了DREM 2.0准确恢复动态调控网络的能力，并使其更容易用于分析具有不同程度相互作用信息的几个物种中的此类网络。DREM 2.0为构建和可视化动态调控网络提供了一个独特的框架。DREM 2.0可从www.sb.cs.cmu.edu/drem下载。
Modeling dynamic regulatory networks is a major challenge since much of the protein-DNA interaction data available is static. The Dynamic Regulatory Events Miner (DREM) uses a Hidden Markov Model-based approach to integrate this static interaction data with time series gene expression leading to models that can determine when transcription factors (TFs) activate genes and what genes they regulate. DREM has been used successfully in diverse areas of biological research. However, several issues were not addressed by the original version. DREM 2.0 is a comprehensive software for reconstructing dynamic regulatory networks that supports interactive graphical or batch mode. With version 2.0 a set of new features that are unique in comparison with other softwares are introduced. First, we provide static interaction data for additional species. Second, DREM 2.0 now accepts continuous binding values and we added a new method to utilize TF expression levels when searching for dynamic models. Third, we added support for discriminative motif discovery, which is particularly powerful for species with limited experimental interaction data. Finally, we improved the visualization to support the new features. Combined, these changes improve the ability of DREM 2.0 to accurately recover dynamic regulatory networks and make it much easier to use it for analyzing such networks in several species with varying degrees of interaction information. DREM 2.0 provides a unique framework for constructing and visualizing dynamic regulatory networks. DREM 2.0 can be downloaded from: www.sb.cs.cmu.edu/drem.
登录
查看更多内容
影响因子：
12.3
作者：
Kuo D;Tan K;Zinman G;Ravasi T;Bar-Joseph Z;Ideker T
通讯作者：
Ideker T
影响因子：
64.8
作者：
通讯作者：
--
邮票：用于探索DNA结合基序相似性的网络工具。
影响因子：
14.9
作者：
Mahony, Shaun;Benos, Panayiotis V
通讯作者：
Benos, Panayiotis V
影响因子：
9.9
作者：
Mendoza-Parra, Marco A.;Walia, Mannu;Sankar, Martial;Gronemeyer, Hinrich
通讯作者：
Gronemeyer, Hinrich
DOI：
10.1073/pnas.2136632100
发表时间：
2003-12-23
影响因子：
11.1
作者：
Liao, JC;Boscolo, R;Roychowdhury, VP
通讯作者：
Roychowdhury, VP