Visualizing Validation of Protein Surface Classifiers
Computer Graphics Forum, Volume 33, Number 3, page 171--180 — Jun 2014
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
@Article{SAMG14, 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" }