scientific visualization

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scientific visualization

Using the computer to display real-world objects that cannot normally be seen, such as the shapes of molecules, air and fluid dynamics and weather patterns. Scientific visualization requires enormous computing resources, and the supercomputer centers and national laboratories throughout the world are always at the forefront of such activity. See visualization.

Visualizing the Structure of Protein
The picture on the left is the x-ray diffraction pattern of an apilopoprotein E3 protein crystal, which plays a major role in cholesterol metabolism. The tiny spots are the x-ray reflections from the crystal, which are used to reconstruct the electron density of atoms (right).

Next Stage - The Structure Model
The colored sticks are the detailed 3-dimensional structure models of the molecule that were fitted into the actual electron density (blue grid-like areas). This stereo image appears 3D when viewed cross-eyed.

The Final Ribbon Model
Using visualization techniques, the overall 3D four-helix bundle structure of the molecule is represented as a ribbon model. The 3D image of this molecule helps researchers better understand it and its interaction with other molecules. (Images courtesy of Dr. Bernhard Rupp, Lawrence Livermore National Laboratory and Dr. Karl H. Weisgraber, Gladstone Institute of Cardiovascular Disease.)
References in periodicals archive ?
2005) came to fruition through InfoVis competitions and attempts to visualize paper and author relationships using recent rendering technology and techniques.
In: Proceedings of IEEE Infovis, 2009, available at: www.
The framework outlined above characterizes the kinds of coordination that can be implemented in a multi-component, multi-view geovisualization environment (or InfoVis environment more generally).
North (eds), INFOVIS 2003: IEEE Symposium on Information Visualization.
In: INFOVIS '05: Proceedings of the 2005 IEEE Symposium on Information Visualization.
We demonstrate our research and the Visual Inquiry Toolkit through an application to a benchmark data set, provided for the IEEE InfoVis 2005 contest (Grinstein et al.
1996a) and InfoVis (Gershon 1992) communities, and some of this work has been explicitly geospatial (Wittenbrink 1995; Dungan et al.
From an InfoVis rather than SciVis perspective, Gershon (1998) took a very different approach than Pang, focusing on kinds of "imperfection" in the information about which an analyst or decision maker might need to know.
While some of the approaches put forward by the InfoVis research community amount to reinventions of the cartographic wheel, others are quite different from traditional cartographic and GIS solutions and should be critically engaged by the GIScience community.
In: Proceedings of InfoVis 2000, October 2000, Salt Lake City, Utah.