Michael Krone, Guido Reina, Christoph Schulz, Tobias Kulschewski, J├╝rgen Pleiss, and Thomas Ertl
J.3 [Computer Applications]: Life and Medical Sciences-Biology and Genetics I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling- Boundary Representations I.4.6 [Image Processing and Computer Vision]: Segmentation-Region Growing
We present a coordinated-view application for the analysis of molecular surface features like cavities, channels and pockets. Our tool employs object-space ambient occlusion for the detection of such features and tracks them over time. It offers time-dependent graphs of metrics concerning those features and allows analyzing the temporal relationship of the features, i.e. when they (dis)appear, split or merge and which features participate in each of these events. The automated analysis process is performed in real time while the user interactively explores a dynamic data set. The system supports linking and brushing to allow for a user-guided visual analysis based on different aspects of the data. We demonstrate the effectiveness of our approach by applying it to data sets from biochemistry and report the insights that can be gained. We also evaluate the benefits of our method with respect to recent advancements in the field. The algorithmic pipeline leverages the computing power of modern GPUs, thus achieving interactive frame rates without any precomputation for fully dynamic data sets.
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