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Keywords:

  • ray casting;
  • visualization;
  • protein data base;
  • atomic representation;
  • I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Raytracing;
  • I.3.6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types;
  • J.3 [Computer Applications]: Life and Medical Sciences—Biology and genetics

Abstract

Molecular visualization is an important tool for analysing the results of biochemical simulations. With modern GPU ray casting approaches, it is only possible to render several million of atoms interactively unless advanced acceleration methods are employed. Whole-cell simulations consist of at least several billion atoms even for simplified cell models. However, many instances of only a few different proteins occur in the intracellular environment, which can be exploited to fit the data into the graphics memory. For each protein species, one model is stored and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes. We present two out-of-core optimizations for the interactive visualization of data sets composed of billions of atoms as well as details on the data preparation and the employed rendering techniques. Furthermore, we apply advanced shading methods to improve the image quality including methods to enhance depth and shape perception besides non-photorealistic rendering methods. We also show that the method can be used to render scenes that are composed of triangulated instances, not only implicit surfaces.