Motivation: Network visualizations of complex biological datasets usually result in 'hairball' images, which do not discriminate network modules. Results: We present the EntOptLayout Cytoscape plug-in based on a recently developed network representation theory. The plug-in provides an efficient visualization of network modules, which represent major protein complexes in protein-protein interaction and signalling networks. Importantly, the tool gives a quality score of the network visualization by calculating the information loss between the input data and the visual representation showing a 3- to 25-fold improvement over conventional methods. Availability and implementation: The plug-in (running on Windows, Linux, or Mac OS) and its tutorial (both in written and video forms) can be downloaded freely under the terms of the MIT license from: http://apps.cytoscape.org/apps/entoptlayout. Supplementary data are available at Bioinformatics online. Contact: csermely.peter@med.semmelweis-univ.hu
翻译:动态: 复杂生物数据集的网络可视化通常产生“ 毛球” 图像, 并不区分网络模块 。 结果 : 我们根据最近开发的网络代表理论, 展示 EntOptLayout Cytoscape 插件 。 插件提供了网络模块的高效可视化, 代表蛋白质- 蛋白质互动和信号网络中的主要蛋白质综合体 。 重要的是, 该工具通过计算输入数据与显示常规方法3至25倍改进的视觉表达方式之间的信息损失, 提供了网络可视化的质量分数 。 可用性和执行性: 插件( 运行在视窗、 Linux 或 Mac OS 上) 及其教程( 以书面和视频形式) 可以根据麻省理工学院的许可条件自由下载 : http://apps. cytoscape.org/ apps/entopotlayout 。 在线生物信息学中可以提供补充数据 。 。 联系: csermely.peter@ med. semmelewelewes- univ.hu. hu. hu.