Visualizing Validation of Protein Surface Classifiers. (12th July 2014)

• Record Type: Journal Article
• Authors: Sarikaya, A.; Albers, D.; Mitchell, J.; Gleicher, M.
• Is Part Of: Computer graphics forum. Volume 33:Number 3(2014)
• Page Start: 171
• Page End: 180
• Publication Date: 2014-07-12
• Subjects: Categories and Subject Descriptors (according to ACM CCS) -- J.3.1 [Computer Applications]: Life and Medical Sciences—Biology and Genetics; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12373
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: 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.