Barlowe, ScottLiu, YujieYang, JingLivesay, Dennis R.Jacobs, Donald J.Mottonen, JamesVerma, DeeptakH. Hauser, H. Pfister, and J. J. van Wijk2014-02-212014-02-2120111467-8659https://doi.org/10.1111/j.1467-8659.2011.01949.xThe 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.I.5.5 [Pattern Recognition]ImplementationInteractive SystemsWaveMap: Interactively Discovering Features From Protein Flexibility Matrices Using Wavelet-based Visual Analytics