Xu Huayong, Yu Hui, Tu Kang, Shi Qianqian, Wei Chaochun, Li Yuan-Yuan, Li Yi-Xue
BMC Syst Biol. 2013;7 Suppl 2(Suppl 2):S7. doi: 10.1186/1752-0509-7-S2-S7. Epub 2013 Oct 14.
We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts.
In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module.
In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.
我们正在见证构建涉及转录因子（TFs）和微小RNA（miRNAs）的组合基因调控网络的方法学取得快速进展。有一些工具可用于完成这些工作，但其中大多数使用起来并不容易，且无法在线获取。特别需要一个网络服务器，以便用户上传实验表达数据集并构建与其特定背景相对应的组合调控网络。
在这项工作中，我们从正向工程流程中汇编了假定的TF-基因、miRNA-基因和TF-miRNA调控关系，并将它们整理为内置数据库。我们简化了用于组合基因调控网络构建的两个独立的正向和反向工程算法的R代码，并将它们形式化为两个主要功能模块。结果，我们发布了cGRNB（组合基因调控网络构建器）：一个通过种子匹配序列信息和基因表达数据集的综合工程来构建组合基因调控网络的网络服务器。cGRNB启用了两个主要的网络构建模块，一个用于miRNA干扰基因表达（MPGE）数据集，另一个用于并行miRNA/mRNA表达数据集。以miRNA为中心的两层组合调控级联是第一个模块的输出，涉及所有三种组合调控类型（TF-基因、TF-miRNA和miRNA-基因）的全面全基因组网络是第二个模块的输出。
在本文中，我们提出了cGRNB，一个通过种子匹配序列信息和基因表达数据集的综合工程来构建组合基因调控网络的网络服务器。由于下一代测序技术的进步，并行miRNA/mRNA表达数据集迅速积累，cGRNB将成为研究人员基于表达数据集构建组合基因调控网络的非常有用的工具。cGRNB网络服务器是免费的，可在http://www.scbit.org/cgrnb在线获取。
