Interactive Visual Analysis of Toponome Data – Lehrstuhl für Visualisierung

In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, new drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample by running cycles of fluorescence tagging with monoclonal antibodies or other affinity reagents, imaging, and bleaching in situ. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per affinity reagent. Biologists are particularly interested in the localization of co-occurring proteins, the frequency of co-occurrence and the distribution of co-occurring proteins across the cell. The goal of this project is to develop an interactive visual analysis approach which supports the biologists in evaluating the multi-parameter fluorescence microscopy data.

The project is carried out in close collaboration with Walter Schubert and Reyk Hillert from the molecular pattern recognition working group at the University of Magdeburg. The graph-based visual analysis was developed together with Helmut Doleisch and Wolfgang Freiler from CD-adapco, Vienna and implemented within the SimVis framework.