
Proceedings Paper
Comparative visualization of protein conformations using large high resolution displays with gestures and body trackingFormat | Member Price | Non-Member Price |
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Paper Abstract
Automatically identifying protein conformations can yield multiple candidate structures. Potential candidates
are examined further to cull false positives. Individual conformations and the collection are compared when
seeking flaws. Desktop displays are ineffective due to limited size and resolution. Thus a user must sacrifice large
scale content by viewing the micro level with high detail or view the macro level while forfeiting small details.
We address this ultimatum by utilizing multiple, high resolution displays. Using 27, 50", high resolution displays
with active, stereoscopic 3D, and modified virtual environment software, each display presents a protein users
can manipulate. Such an environment enables users to gain extensive insight both at the micro and macro levels
when performing structural comparisons among the candidate structures. Integrating stereoscopic 3D improves
the user’s ability to judge conformations spatial relationships. In order to facilitate intuitive interaction, gesture
recognition as well as body tracking are used. The user is able to look at the protein of interest, select a
modality via gesture, and the user’s motions provide intuitive navigation functions such as panning, rotating,
and zooming. Using this approach, users are able to perform protein structure comparison through intuitive
controls without sacrificing important visual details at any scale.
Paper Details
Date Published: 8 February 2015
PDF: 13 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970E (8 February 2015); doi: 10.1117/12.2079766
Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)
PDF: 13 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970E (8 February 2015); doi: 10.1117/12.2079766
Show Author Affiliations
Matt Marangoni, Wright State Univ. (United States)
Thomas Wischgoll, Wright State Univ. (United States)
Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)
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