Atomistic Visualization of Mesoscopic Whole-Cell Simulations Using Ray-Casted Instancing

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dc.contributor.authorFalk, Martinen_US
dc.contributor.authorKrone, Michaelen_US
dc.contributor.authorErtl, Thomasen_US
dc.contributor.editorHolly Rushmeier and Oliver Deussenen_US
dc.date.accessioned2015-02-28T16:16:26Z
dc.date.available2015-02-28T16:16:26Z
dc.date.issued2013en_US
dc.description.abstractMolecular visualization is an important tool for analysing the results of biochemical simulations. With modern GPU ray casting approaches, it is only possible to render several million of atoms interactively unless advanced acceleration methods are employed. Whole‐cell simulations consist of at least several billion atoms even for simplified cell models. However, many instances of only a few different proteins occur in the intracellular environment, which can be exploited to fit the data into the graphics memory. For each protein species, one model is stored and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes. We present two out‐of‐core optimizations for the interactive visualization of data sets composed of billions of atoms as well as details on the data preparation and the employed rendering techniques. Furthermore, we apply advanced shading methods to improve the image quality including methods to enhance depth and shape perception besides non‐photorealistic rendering methods. We also show that the method can be used to render scenes that are composed of triangulated instances, not only implicit surfaces.Molecular visualization is an important tool for analyzing the results of biochemical simulations. With modern GPU ray casting approaches it is only possible to render several million of atoms interactively unless advanced acceleration methods are employed. Whole‐cell simulations consist of at least several billion atoms even for simplified cell models. However, many instances of only a few different proteins occur in the intracellular environment, which can be exploited to fit the data into the graphics memory. For each protein species, one model is stored and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes with implicit surfaces and triangular meshes.en_US
dc.description.number8
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume32
dc.identifier.doi10.1111/cgf.12197en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12197en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectray castingen_US
dc.subjectvisualizationen_US
dc.subjectprotein data baseen_US
dc.subjectatomic representationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree‐Dimensional Graphics and Realism—Raytracingen_US
dc.subjectI.3.6 [Computer Graphics]en_US
dc.subjectMethodology and Techniques—Graphics data structures and data typesen_US
dc.subjectJ.3 [Computer Applications]en_US
dc.subjectLife and Medical Sciences—Biology and geneticsen_US
dc.titleAtomistic Visualization of Mesoscopic Whole-Cell Simulations Using Ray-Casted Instancingen_US
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