dc.contributor.author | Barlowe, Scott | en_US |
dc.contributor.author | Liu, Yujie | en_US |
dc.contributor.author | Yang, Jing | en_US |
dc.contributor.author | Livesay, Dennis R. | en_US |
dc.contributor.author | Jacobs, Donald J. | en_US |
dc.contributor.author | Mottonen, James | en_US |
dc.contributor.author | Verma, Deeptak | en_US |
dc.contributor.editor | H. Hauser, H. Pfister, and J. J. van Wijk | en_US |
dc.date.accessioned | 2014-02-21T20:23:43Z | |
dc.date.available | 2014-02-21T20:23:43Z | |
dc.date.issued | 2011 | en_US |
dc.identifier.issn | 1467-8659 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1111/j.1467-8659.2011.01949.x | en_US |
dc.description.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. | en_US |
dc.publisher | The Eurographics Association and Blackwell Publishing Ltd. | en_US |
dc.subject | I.5.5 [Pattern Recognition] | en_US |
dc.subject | Implementation | en_US |
dc.subject | Interactive Systems | en_US |
dc.title | WaveMap: Interactively Discovering Features From Protein Flexibility Matrices Using Wavelet-based Visual Analytics | en_US |
dc.description.seriesinformation | Computer Graphics Forum | en_US |
dc.description.volume | 30 | en_US |
dc.description.number | 3 | en_US |