GPU-powered tools boost molecular visualization.

Matthieu Chavent 1, 2, 3 Bruno Lévy 2 Michael Krone 4 Katrin Bidmon 4 Jean-Philippe Nominé 5 Thomas Ertl 6 Marc Baaden 3, *
* Corresponding author
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 ALICE - Geometry and Lighting
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Recent advances in experimental structure determination provide a wealth of structural data on huge macromolecular assemblies such as the ribosome or viral capsids, available in public databases. Further structural models arise from reconstructions using symmetry orders or fitting crystal structures into low-resolution maps obtained by electron-microscopy or small angle X-ray scattering experiments. Visual inspection of these huge structures remains an important way of unravelling some of their secrets. However, such visualization cannot conveniently be carried out using conventional rendering approaches, either due to performance limitations or due to lack of realism. Recent developments, in particular drawing benefit from the capabilities of Graphics Processing Units (GPUs), herald the next generation of molecular visualization solutions addressing these issues. In this article, we present advances in computer science and visualization that help biologists visualize, understand and manipulate large and complex molecular systems, introducing concepts that remain little-known in the bioinformatics field. Furthermore, we compile currently available software and methods enhancing the shape perception of such macromolecular assemblies, for example based on surface simplification or lighting ameliorations.
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Submitted on : Saturday, November 26, 2011 - 11:50:38 PM
Last modification on : Wednesday, July 10, 2019 - 7:18:03 PM

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Matthieu Chavent, Bruno Lévy, Michael Krone, Katrin Bidmon, Jean-Philippe Nominé, et al.. GPU-powered tools boost molecular visualization.. Briefings in Bioinformatics, Oxford University Press (OUP), 2011, 12 (6), pp.689-701. ⟨10.1093/bib/bbq089⟩. ⟨hal-00645161⟩



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