The cover image shows a visualization of a Chaperone protein. An objective in the analysis of this protein is how atoms and other molecules interact with the protein and enter its inner part. A distance field describes the greatest distance between each component of the protein. Following the paths of maximal distance, atoms can enter and leave the inner part. The narrow points of these paths define thereby the maximal size of an atom. The aim of this analysis is to detect all of these narrow points as well as the voids of the distance field. The voids and narrow points are the maxima and saddles in the distance field that can be extracted using discrete Morse theory. However, the distance field is very rich structured and contains dominant and spurious maxima and saddles. An importance measure that allows to reliable distinguish between them is 'persistence'. However, computing persistence requires huge memory consumption. This data set is of dimension 1120 × 1131 × 1552, and the standard persistence approach would require about 500 GB of memory. An improved version of persistence computation makes use of the underlying Morse-Smale complex, which can be seen as a sparse representation of the distance field. Using this complex, the overall memory consumption can be reduced to 14 GB and persistence can be computed on commodity hardware. The visualization shows the maxima of the distance field as red spheres scaled by persistence. The saddles -- narrow points -- are shown as yellow glowing spheres. Their strength is also proportional to their persistence. An isolevel of the distance field is depicted as gray transparent surface.
Our visualization of a Chaperon protein was chosen to be the cover image of the February issue vol. 01/35 of the journal Informatik Spektrum. Don’t miss this issue!