From Atoms to Cells: Interactive and Illustrative Visualization of Digitally Reproduced Lifeforms

Mathieu Le Muzic
From Atoms to Cells: Interactive and Illustrative Visualization of Digitally Reproduced Lifeforms
Supervisor: Ivan Viola
Duration: 2013-2016
[image] [PhD-Thesis]

Information

Abstract

Macromolecules, such as proteins, are the building blocks of the machinery of life, and therefore are essential to the comprehension of physiological processes. In physiology, illustrations and animations are often utilized as a mean of communication because they can easily be understood with little background knowledge. However, their realization requires numerous months of manual work, which is both expensive and time consuming. Computational biology experts produce everyday large amount of data that is publicly available and that contains valuable information about the structure and also the function of these macromolecules. Instead of relying on manual work to generate illustrative visualizations of the cell biology, we envision a solution that would utilize all the data already available in order to streamline the creation process. In this thesis are presented several contributions that aim at enabling our vision. First, a novel GPU-based rendering pipeline that allows interactive visualization of realistic molecular datasets comprising up to hundreds of millions of macromolecules. The rendering pipeline is embedded into a popular game engine and well known computer graphics optimizations were adapted to support this type of data, such as level-of-detail, instancing and occlusion queries. Secondly, a new method for authoring cutaway views and improving spatial exploration of crowded molecular landscapes. The system relies on the use of clipping objects that are manually placed in the scene and on visibility equalizers that allows fine tuning of the visibility of each species present in the scene. Agent-based modeling produces trajectory data that can also be combined with structural information in order to animate these landscapes. The snapshots of the trajectories are often played in fast-forward to shorten the length of the visualized sequences, which also renders potentially interesting events occurring at a higher temporal resolution invisible. The third contribution is a solution to visualize time-lapse of agent-based simulations that also reveals hidden information that is only observable at higher temporal resolutions. And finally, a new type of particle-system that utilize quantitative models as input and generate missing spatial information to enable the visualization of molecular trajectories and interactions. The particle-system produces a similar visual output as traditional agent-based modeling tools for a much lower computational footprint and allows interactive changing of the simulation parameters, which was not achievable with previous methods.

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BibTeX

@phdthesis{LeMuzic_2016_PhD,
  title =      "From Atoms to Cells: Interactive and Illustrative
               Visualization of Digitally Reproduced Lifeforms",
  author =     "Mathieu Le Muzic",
  year =       "2016",
  abstract =   "Macromolecules, such as proteins, are the building blocks of
               the machinery of life, and therefore are essential to the
               comprehension of physiological processes. In physiology,
               illustrations and animations are often utilized as a mean of
               communication because they can easily be understood with
               little background knowledge. However, their realization
               requires numerous months of manual work, which is both
               expensive and time consuming. Computational biology experts
               produce everyday large amount of data that is publicly
               available and that contains valuable information about the
               structure and also the function of these macromolecules.
               Instead of relying on manual work to generate illustrative
               visualizations of the cell biology, we envision a solution
               that would utilize all the data already available in order
               to streamline the creation process. In this thesis are
               presented several contributions that aim at enabling our
               vision. First, a novel GPU-based rendering pipeline that
               allows interactive visualization of realistic molecular
               datasets comprising up to hundreds of millions of
               macromolecules. The rendering pipeline is embedded into a
               popular game engine and well known computer graphics
               optimizations were adapted to support this type of data,
               such as level-of-detail, instancing and occlusion queries.
               Secondly, a new method for authoring cutaway views and
               improving spatial exploration of crowded molecular
               landscapes. The system relies on the use of clipping objects
               that are manually placed in the scene and on visibility
               equalizers that allows fine tuning of the visibility of each
               species present in the scene. Agent-based modeling produces
               trajectory data that can also be combined with structural
               information in order to animate these landscapes. The
               snapshots of the trajectories are often played in
               fast-forward to shorten the length of the visualized
               sequences, which also renders potentially interesting events
               occurring at a higher temporal resolution invisible. The
               third contribution is a solution to visualize time-lapse of
               agent-based simulations that also reveals hidden information
               that is only observable at higher temporal resolutions. And
               finally, a new type of particle-system that utilize
               quantitative models as input and generate missing spatial
               information to enable the visualization of molecular
               trajectories and interactions. The particle-system produces
               a similar visual output as traditional agent-based modeling
               tools for a much lower computational footprint and allows
               interactive changing of the simulation parameters, which was
               not achievable with previous methods.",
  month =      oct,
  address =    "Favoritenstrasse 9-11/186, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2016/LeMuzic_2016_PhD/",
}