Department of Computer Sciences, Brown University, Providence, RI 02912, USA.
IEEE Trans Vis Comput Graph. 2010 Jul-Aug;16(4):609-20. doi: 10.1109/TVCG.2009.106.
We introduce several novel visualization and interaction paradigms for visual analysis of published protein-protein interaction networks, canonical signaling pathway models, and quantitative proteomic data. We evaluate them anecdotally with domain scientists to demonstrate their ability to accelerate the proteomic analysis process. Our results suggest that structuring protein interaction networks around canonical signaling pathway models, exploring pathways globally and locally at the same time, and driving the analysis primarily by the experimental data, all accelerate the understanding of protein pathways. Concrete proteomic discoveries within T-cells, mast cells, and the insulin signaling pathway validate the findings. The aim of the paper is to introduce novel protein network visualization paradigms and anecdotally assess the opportunity of incorporating them into established proteomic applications. We also make available a prototype implementation of our methods, to be used and evaluated by the proteomic community.
我们介绍了几种新颖的可视化和交互范例,用于对已发表的蛋白质-蛋白质相互作用网络、规范信号通路模型和定量蛋白质组学数据进行可视化分析。我们通过与领域科学家进行评估来证明它们能够加速蛋白质组学分析过程。我们的结果表明,围绕规范信号通路模型构建蛋白质相互作用网络、同时全局和局部地探索途径以及主要通过实验数据驱动分析,都可以加速对蛋白质途径的理解。T 细胞、肥大细胞和胰岛素信号通路中的具体蛋白质组学发现验证了这些发现。本文的目的是介绍新颖的蛋白质网络可视化范例,并通过实例评估将它们纳入现有的蛋白质组学应用中的机会。我们还提供了我们方法的原型实现,供蛋白质组学社区使用和评估。