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Visualizing Validation of Protein Surface Classifiers

Computer Graphics Forum, Volume 33, Number 3, page 171--180 — Jun 2014
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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.

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BibTex references

  author       = "Sarikaya, Alper and Albers, Danielle and Mitchell, Julie C. and Gleicher, Michael",
  title        = "Visualizing Validation of Protein Surface Classifiers",
  journal      = "Computer Graphics Forum",
  number       = "3",
  volume       = "33",
  pages        = "171--180",
  month        = "Jun",
  year         = "2014",
  pmcid        = "PMC4204728",
  ee           = "http://onlinelibrary.wiley.com/doi/10.1111/cgf.12373/abstract",
  doi          = "10.1111/cgf.12373",
  projecturl   = "http://graphics.cs.wisc.edu/Vis/PSCVis/",
  url          = "http://graphics.cs.wisc.edu/Papers/2014/SAMG14"

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