Department of Microbiology, Immunology and Biochemistry and Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
Bioinformatics. 2013 Nov 1;29(21):2801-3. doi: 10.1093/bioinformatics/btt472. Epub 2013 Aug 21.
The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships.
BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW).
Supplementary data are available at Bioinformatics online.
贝叶斯网络网络服务器(BNW)是一个用于系统遗传学和其他生物数据集的综合网络建模的平台。它允许用户快速、无缝地上传数据集,学习最能解释数据的网络模型的结构,并使用该模型来理解网络变量之间的关系。许多数据集,包括用于创建遗传网络模型的数据集,都包含离散(例如基因型)和连续(例如基因表达特征)变量,BNW 允许对混合数据集进行建模。BNW 的用户可以通过易于使用的结构约束界面在结构学习过程中纳入先验知识。在结构学习之后,用户会立即呈现一个交互式网络模型,可用于对网络关系做出可测试的假设。
包括可下载的结构学习包在内的 BNW 可在 http://compbio.uthsc.edu/BNW 上获得。(BNW 添加结构约束的界面使用的 HTML5 功能不受当前版本 Internet Explorer 的支持。我们建议在访问 BNW 时使用其他浏览器(例如 Google Chrome 或 Mozilla Firefox)。)
补充数据可在 Bioinformatics 在线获得。