WaveMap: interactively discovering features from protein flexibility matrices usingwavelet-based visual analytics

Authors:
Scott Barlowe;Yujie Liu;Jing Yang;Dennis R. Livesay;Donald J. Jacobs;James Mottonen;Deeptak Verma
Affiliations:
Dept. of Computer Science, University of North Carolina at Charlotte;Dept. of Computer Science, University of North Carolina at Charlotte;Dept. of Computer Science, University of North Carolina at Charlotte;Dept. of Bioinformatics and Genomics, University of North Carolina at Charlotte;Dept. of Physics and Optical Science, University of North Carolina at Charlotte;Dept. of Physics and Optical Science, University of North Carolina at Charlotte;Dept. of Bioinformatics and Genomics, University of North Carolina at Charlotte
Venue:
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Year:
2011

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Abstract

The knowledge gained from biology datasets can streamline and speed-up pharmaceutical development. However, computational models generate so much information regarding protein behavior that large-scale analysis by traditional methods is almost impossible. The volume of data produced makes the transition from data to knowledge difficult and hinders biomedical advances. In this work, we present a novel visual analytics approach named WaveMap for exploring data generated by a protein flexibility model. WaveMap integrates wavelet analysis, visualizations, and interactions to facilitate the browsing, feature identification, and comparison of protein attributes represented by two-dimensional plots. We have implemented a fully working prototype of WaveMap and illustrate its usefulness through expert evaluation and an example scenario.