Understanding how objects change or move is a challenge across many scientific and engineering disciplines. As available computational power and working memory increase it is becoming possible to explore potential changes in more complex systems through simulations at timescales that were previously thought impossible. Furthermore, simulations that previously were only possible on supercomputers are now possible on standard desktop equipment. This is especially true in the fields of structural biology and related disciplines where computational simulations are often used to predict potential movements or changes of proteins. This dissertation describes tools and techniques that aim to help researchers more effectively and efficiently understand the results of these simulations with the help of visualization, analysis and interaction. The first two of these tools are intended to help researchers more effectively and efficiently visualize and analyze the results of course grained normal mode analysis. First, I improved static visualization of protein flexibility by using affine motion models and hierarchical clustering to model the coordinated motion of groups of residues and draw to arrows showing the direction of movement of these groups. Second, I used these affine motion models and clustering techniques to create improved trajectories of the motion of protein molecules. Finally, I developed a novel system for enabling group discussion and visualization of proteins and their motions on large stereo displays.

@PhdThesis{Bry11,
  author       = "Bryden, Aaron",
  title        = "Visualization and Analysis of Protein Flexibility",
  school       = "University of Wisconsin Madison",
  year         = "2011",
  url          = "http://graphics.cs.wisc.edu/Papers/2011/Bry11"
}