Speaker: Sorger Johannes (ICGA)
We propose a method that deals with the visualization of incomplete data information in developmental or evolutionary states of biological models, such as viruses or microorganisms. The benefit of our method is that it provides a possibility to create animated transitions that properly illustrate biological processes without having exact models of them.
A challenging problem in biology the incompleteness of acquired information when visualizing biological phenomena. Structural biology generates detailed models of viruses or bacteria at different development stages, while the processes that relate one stage to another are often not clear. Similarly, the entire life cycle of a biological entity might be available as a quantitative model, while only one structural model is available. If the relation between two models is specified at a lower level of detail than the actual models themselves, the two models cannot be interpolated correctly. We propose a method that deals with the visualization of incomplete data information in the developmental or evolutionary states of biological mesoscale models, such as viruses or microorganisms. The central tool in our approach is visual abstraction. Instead of directly interpolating between two models that show different states of an organism, we gradually forward transform the models into a level of visual abstraction that matches the level of detail of the modeled relation between them. At this level, the models can be interpolated without conveying false information. After the interpolation to the new state, we apply the inverse transformation to the model's original level of abstraction. To show the flexibility of our approach, we demonstrate our method on the basis of molecular data, in particular data of the HIV virion and the mycoplasma bacterium.