BC Cancer Research Center, Vancouver, Canada.
Brief Bioinform. 2012 Sep;13(5):627-44. doi: 10.1093/bib/bbr069. Epub 2011 Dec 9.
Networks are typically visualized with force-based or spectral layouts. These algorithms lack reproducibility and perceptual uniformity because they do not use a node coordinate system. The layouts can be difficult to interpret and are unsuitable for assessing differences in networks. To address these issues, we introduce hive plots (http://www.hiveplot.com) for generating informative, quantitative and comparable network layouts. Hive plots depict network structure transparently, are simple to understand and can be easily tuned to identify patterns of interest. The method is computationally straightforward, scales well and is amenable to a plugin for existing tools.
网络通常使用基于力的或谱布局进行可视化。这些算法缺乏可重复性和感知一致性，因为它们不使用节点坐标系。这些布局可能难以解释，不适合评估网络之间的差异。为了解决这些问题，我们引入了蜂巢图（http://www.hiveplot.com）来生成信息丰富、定量和可比的网络布局。蜂巢图透明地描绘网络结构，易于理解，并且可以轻松调整以识别感兴趣的模式。该方法计算简单，扩展性好，并且可以适用于现有工具的插件。
