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.

中文翻译：

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一种探索生物医学知识的多尺度可视化分析方法

本文描述了一种正在进行的多尺度可视化分析方法，用于大规模探索和分析生物医学知识。我们利用全局和局部视图、分层和基于流的图形布局、多面搜索、邻域推荐和文档可视化以交互方式帮助研究人员在生物医学知识的背景下探索、查询和分析生物图谱。我们的方法的通用性——只要它只需要链接到文档的知识图——意味着它可以支持不同领域的一系列治疗用例，从疾病传播到药物发现。与领域专家的早期互动支持我们使用具有超过 40,000 个节点和 350,000 条边的图的用例的方法。