Visualizing Validation of Protein Surface Classifiers.

Many bioinformatics applications construct classifiers that are validated in experiments that compare their results to known ground truth over a corpus. In this paper, we introduce an approach for exploring the results of such classifier validation experiments, focusing on classifiers for regions of molecular surfaces. We provide a tool that allows for examining classification performance patterns over a test corpus. The approach combines a summary view that provides information about an entire corpus of molecules with a detail view that visualizes classifier results directly on protein surfaces. Rather than displaying miniature 3D views of each molecule, the summary provides 2D glyphs of each protein surface arranged in a reorderable, small-multiples grid. Each summary is specifically designed to support visual aggregation to allow the viewer to both get a sense of aggregate properties as well as the details that form them. The detail view provides a 3D visualization of each protein surface coupled with interaction techniques designed to support key tasks, including spatial aggregation and automated camera touring. A prototype implementation of our approach is demonstrated on protein surface classifier experiments.

Automated Illustration of Molecular Flexibility.

In this paper, we present an approach to creating illustrations of molecular flexibility using normal mode analysis (NMA). The output of NMA is a collection of points corresponding to the locations of atoms and associated motion vectors, where a vector for each point is known. Our approach abstracts the complex object and its motion by grouping the points, models the motion of each group as an affine velocity, and depicts the motion of each group by automatically choosing glyphs such as arrows. Affine exponentials allow the extrapolation of nonlinear effects such as near rotations and spirals from the linear velocities. Our approach automatically groups points by finding sets of neighboring points whose motions fit the motion model. The geometry and motion models for each group are used to determine glyphs that depict the motion, with various aspects of the motion mapped to each glyph. We evaluated the utility of our system in real work done by structural biologists both by utilizing it in our own structural biology work and quantitatively measuring its usefulness on a set of known protein conformation changes. Additionally, in order to allow ourselves and our collaborators to effectively use our techniques we integrated our system with commonly used tools for molecular visualization.