The project develops new techniques for the interactive navigtion, visualization, and analysis of heterogeneous biological networks

该项目的目标是为网络环境下的生物数据开发新的可视化分析技术。可视化分析框架的核心组件是用于数据集成的自动化方法、高效的数据分析方法和复杂的图形绘制技术。通过使用扩展的BioPAX模型，数据集成将得到大力支持和简化。新的可视化分析技术将使用户能够将高通量数据（转录组学，蛋白质组学，代谢组学）映射到几个公共数据库的统一网络数据上，并以高效和有效的方式进行具有挑战性的分析。针对各种临床应用（例如，个性化癌症治疗）的定制数据可视化分析工具将使医疗环境中这些高通量数据集的有效分析成为可能。第一个资助期的重点是为生物网络的可视化分析框架奠定基础，与此相反，第二个资助期将集中于使该框架更接近应用。与选定的合作伙伴一起，我们将把可视化分析带到医生的办公桌上。

The objective of this project is the development of novel visual analytics techniques for biological data in the context of networks. The core components of the visual analytics framework are automated methods for data integration, efficient data analysis methods, and sophisticated graph drawing techniques. Data integration will be strongly supported and simplified by using an extended BioPAX model. The novel visual analytics techniques will enable users to map high-throughput data (transcriptomics, proteomics, metabolomics) onto the unified network data of several public databases and to carry out challenging analyses in an efficient and effective way. Customized data visual analytics tools for various clinical applications (e.g., personalized cancer therapy) will enable the efficient analysis of these high-throughput data sets in medical settings. In contrast to the first funding period, where the focus was on laying the foundations of a visual analytics framework for biological networks, the second period will concentrate on bringing this framework closer to the application. Together with selected collaboration partners we will literally bring visual analytics to the physician’s desk.