This paper describes an ongoing multi-scale visual analytics approach for exploring and analyzing biomedical knowledge at scale.We utilize global and local views, hierarchical and flow-based graph layouts, multi-faceted search, neighborhood recommendations, and document visualizations to help researchers interactively explore, query, and analyze biological graphs against the backdrop of biomedical knowledge. The generality of our approach - insofar as it re-quires only knowledge graphs linked to documents - means it can support a range of therapeutic use cases across different domains, from disease propagation to drug discovery. Early interactions with domain experts support our approach for use cases with graphs with over 40,000 nodes and 350,000 edges.

翻译：本文介绍目前大规模探讨和分析生物医学知识的多尺度视觉分析方法。 我们利用全球和当地观点、等级和流动图表布局、多面搜索、邻里建议和文件可视化来帮助研究人员在生物医学知识背景下互动探索、查询和分析生物图。我们的方法的概括性――只要重新要求与文件相关的知识图――意味着它能够支持从疾病传播到毒品发现等不同领域的一系列治疗性使用案例。我们与域专家的早期互动支持我们使用有40,000多个节点和350,000个边缘的图表的案例。