GPU-powered tools boost molecular visualization.
Identifieur interne : 002541 ( Hal/Corpus ); précédent : 002540; suivant : 002542GPU-powered tools boost molecular visualization.
Auteurs : Matthieu Chavent ; Bruno Lévy ; Michael Krone ; Katrin Bidmon ; Jean-Philippe Nominé ; Thomas Ertl ; Marc BaadenSource :
- Briefings in Bioinformatics [ 1467-5463 ] ; 2011-11.
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.
Url:
DOI: 10.1093/bib/bbq089
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Hal:hal-00645161Le document en format XML
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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.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">GPU-powered tools boost molecular visualization.</title><author role="aut"><persName><forename type="first">Matthieu</forename><surname>Chavent</surname></persName><email></email><idno type="halauthor">367427</idno><affiliation ref="#struct-2358"></affiliation><affiliation ref="#struct-3174"></affiliation><affiliation ref="#struct-489"></affiliation></author><author role="aut"><persName><forename type="first">Bruno</forename><surname>Lévy</surname></persName><email></email><idno type="idhal">bruno-levy</idno><idno type="halauthor">136961</idno><idno type="arXiv">http://arxiv.org/a/brlevy</idno><affiliation ref="#struct-3174"></affiliation></author><author role="aut"><persName><forename type="first">Michael</forename><surname>Krone</surname></persName><email></email><idno type="halauthor">663136</idno><affiliation ref="#struct-203650"></affiliation></author><author role="aut"><persName><forename type="first">Katrin</forename><surname>Bidmon</surname></persName><email></email><idno type="halauthor">663137</idno><affiliation ref="#struct-203650"></affiliation></author><author role="aut"><persName><forename type="first">Jean-Philippe</forename><surname>Nominé</surname></persName><email></email><idno type="halauthor">663138</idno><affiliation ref="#struct-40214"></affiliation></author><author role="aut"><persName><forename type="first">Thomas</forename><surname>Ertl</surname></persName><email></email><idno type="halauthor">663139</idno><affiliation ref="#struct-63008"></affiliation></author><author role="crp"><persName><forename type="first">Marc</forename><surname>Baaden</surname></persName><email>baaden@smplinux.de</email><ptr type="url" target="http://www.baaden.ibpc.fr"></ptr><idno type="halauthor">663134</idno><affiliation ref="#struct-489"></affiliation></author><editor role="depositor"><persName><forename>Marc</forename><surname>Baaden</surname></persName><email>baaden@smplinux.de</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2011-11-26 23:50:38</date><date type="whenModified">2016-05-18 08:54:48</date><date type="whenReleased">2011-11-26 23:50:38</date><date type="whenProduced">2011-11</date></edition><respStmt><resp>contributor</resp><name key="104717"><persName><forename>Marc</forename><surname>Baaden</surname></persName><email>baaden@smplinux.de</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00645161</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00645161</idno><idno type="halBibtex">chavent:hal-00645161</idno><idno type="halRefHtml">Briefings in Bioinformatics, Oxford University Press (OUP), 2011, 12 (6), pp.689-701. <10.1093/bib/bbq089></idno><idno type="halRef">Briefings in Bioinformatics, Oxford University Press (OUP), 2011, 12 (6), pp.689-701. <10.1093/bib/bbq089></idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-PARIS7">Université Denis Diderot - Paris VII</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-ACGI" p="LORIA">Algorithmique, calcul, image et géométrie</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="CEA">CEA - Commissariat à l'énergie atomique</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INC-CNRS">Institut de Chimie du CNRS</idno><idno type="stamp" n="DRT" p="CEA">Direction de la recherche technologique</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">GPU-powered tools boost molecular visualization.</title><author role="aut"><persName><forename type="first">Matthieu</forename><surname>Chavent</surname></persName><idno type="halAuthorId">367427</idno><affiliation ref="#struct-2358"></affiliation><affiliation ref="#struct-3174"></affiliation><affiliation ref="#struct-489"></affiliation></author><author role="aut"><persName><forename type="first">Bruno</forename><surname>Lévy</surname></persName><idno type="idHal">bruno-levy</idno><idno type="halAuthorId">136961</idno><idno type="arXiv">http://arxiv.org/a/brlevy</idno><affiliation ref="#struct-3174"></affiliation></author><author role="aut"><persName><forename type="first">Michael</forename><surname>Krone</surname></persName><idno type="halAuthorId">663136</idno><affiliation ref="#struct-203650"></affiliation></author><author role="aut"><persName><forename type="first">Katrin</forename><surname>Bidmon</surname></persName><idno type="halAuthorId">663137</idno><affiliation ref="#struct-203650"></affiliation></author><author role="aut"><persName><forename type="first">Jean-Philippe</forename><surname>Nominé</surname></persName><idno type="halAuthorId">663138</idno><affiliation ref="#struct-40214"></affiliation></author><author role="aut"><persName><forename type="first">Thomas</forename><surname>Ertl</surname></persName><idno type="halAuthorId">663139</idno><affiliation ref="#struct-63008"></affiliation></author><author role="crp"><persName><forename type="first">Marc</forename><surname>Baaden</surname></persName><email>baaden@smplinux.de</email><ptr type="url" target="http://www.baaden.ibpc.fr"></ptr><idno type="halAuthorId">663134</idno><affiliation ref="#struct-489"></affiliation></author></analytic><monogr><idno type="halJournalId" status="VALID">11302</idno><idno type="issn">1467-5463</idno><idno type="eissn">1477-4054</idno><title level="j">Briefings in Bioinformatics</title><imprint><publisher>Oxford University Press (OUP)</publisher><biblScope unit="volume">12</biblScope><biblScope unit="issue">6</biblScope><biblScope unit="pp">689-701</biblScope><date type="datePub">2011-11</date><date type="dateEpub">2011-02-09</date></imprint></monogr><idno type="doi">10.1093/bib/bbq089</idno><idno type="pubmed">21310717</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><classCode scheme="halDomain" n="sdv.bbm">Life Sciences [q-bio]/Biochemistry, Molecular Biology</classCode><classCode scheme="halTypology" n="ART">Journal articles</classCode></textClass><abstract xml:lang="en">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.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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