Two-level approach to efficient visualization of protein dynamics

On Evaluating Runtime Performance of Interactive Visualizations

As our field matures, evaluation of visualization techniques has extended from reporting runtime performance to studying user behavior. Consequently, many methodologies and best practices for user studies have evolved. While maintaining interactivity continues to be crucial for the exploration of large data sets, no similar methodological foundation for evaluating runtime performance has been developed. Our analysis of 50 recent visualization papers on new or improved techniques for rendering volumes or particles indicates that only a very limited set of parameters like different data sets, camera paths, viewport sizes, and GPUs are investigated, which make comparison with other techniques or generalization to other parameter ranges at least questionable. To derive a deeper understanding of qualitative runtime behavior and quantitative parameter dependencies, we developed a framework for the most exhaustive performance evaluation of volume and particle visualization techniques that we are aware of, including millions of measurements on ten different GPUs. This paper reports on our insights from statistical analysis of this data, discussing independent and linear parameter behavior and non-obvious effects. We give recommendations for best practices when evaluating runtime performance of scientific visualization applications, which can serve as a starting point for more elaborate models of performance quantification.

Ellipsoidal Abstract and Illustrative Representations of Molecular Surfaces

Molecular visualization is often challenged with rendering of large molecular structures in real time. The key to LOD (level-of-detail), a classical technology, lies in designing a series of hierarchical abstractions of protein. In the paper, we improved the smoothness of transition for these abstractions by constructing a complete binary tree of a protein. In order to reduce the degree of expansion of the geometric model corresponding to the high level of abstraction, we introduced minimum ellipsoidal enveloping and some post-processing techniques. At the same time, a simple, ellipsoid drawing method based on graphics processing unit (GPU) is used that can guarantee that the drawing speed is not lower than the existing sphere-drawing method. Finally, we evaluated the rendering performance and effect on series of molecules with different scales. The post-processing techniques applied, diffuse shading and contours, further conceal the expansion problem and highlight the surface details.

Multiscale Molecular Visualization

We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basics and describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the general structure of the following survey. First, we discuss methods that support the visual analysis of molecular dynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the second part, we survey multiscale approaches that support the design, analysis, and manipulation of DNA nanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, and navigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches that support interactive exploration within large structural biology assemblies up to the size of bacterial cells. We describe fundamental rendering techniques as well as approaches for element instantiation, visibility management, visual guidance, camera control, and support of depth perception. We close the survey with a brief listing of important tools that implement many of the discussed approaches and a conclusion that provides some research challenges in the field.

Molecular Dynamics Visualization (MDV): Stereoscopic 3D Display of Biomolecular Structure and Interactions Using the Unity Game Engine

Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.

Chameleon: Dynamic Color Mapping for Multi-Scale Structural Biology Models

Visualization of structural biology data uses color to categorize or separate dense structures into particular semantic units. In multiscale models of viruses or bacteria, there are atoms on the finest level of detail, then amino-acids, secondary structures, macromolecules, up to the compartment level and, in all these levels, elements can be visually distinguished by color. However, currently only single scale coloring schemes are utilized that show information for one particular scale only. We present a novel technology which adaptively, based on the current scale level, adjusts the color scheme to depict or distinguish the currently best visible structural information. We treat the color as a visual resource that is distributed given a particular demand. The changes of the color scheme are seamlessly interpolated between the color scheme from the previous views into a given new one. With such dynamic multi-scale color mapping we ensure that the viewer is able to distinguish structural detail that is shown on any given scale. This technique has been tested by users with an expertise in structural biology and has been overall well received.

Physics-Based Visual Characterization of Molecular Interaction Forces

Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.

Real-Time Molecular Visualization Supporting Diffuse Interreflections and Ambient Occlusion

Today molecular simulations produce complex data sets capturing the interactions of molecules in detail. Due to the complexity of this time-varying data, advanced visualization techniques are required to support its visual analysis. Current molecular visualization techniques utilize ambient occlusion as a global illumination approximation to improve spatial comprehension. Besides these shadow-like effects, interreflections are also known to improve the spatial comprehension of complex geometric structures. Unfortunately, the inherent computational complexity of interreflections would forbid interactive exploration, which is mandatory in many scenarios dealing with static and time-varying data. In this paper, we introduce a novel analytic approach for capturing interreflections of molecular structures in real-time. By exploiting the knowledge of the underlying space filling representations, we are able to reduce the required parameters and can thus apply symbolic regression to obtain an analytic expression for interreflections. We show how to obtain the data required for the symbolic regression analysis, and how to exploit our analytic solution to enhance interactive molecular visualizations.

The Representation and Parametrization of Orthogonal Matrices

Four representations and parametrizations of orthogonal matrices Q ∈ R(m×n) in terms of the minimal number of essential parameters {φ} are discussed: the exponential representation, the Householder reflector representation, the Givens rotation representation, and the rational Cayley transform representation. Both square n = m and rectangular n < m situations are considered. Two separate kinds of parametrizations are considered: one in which the individual columns of Q are distinct, the Stiefel manifold, and the other in which only span(Q) is significant, the Grassmann manifold. The practical issues of numerical stability, continuity, and uniqueness are discussed. The computation of Q in terms of the essential parameters {φ}, and also the extraction of {φ} for a given Q are considered for all of the parametrizations. The transformation of gradient arrays between the Q and {φ} variables is discussed for all representations. It is our hope that developers of new methods will benefit from this comparative presentation of an important but rarely analyzed subject.

MegaMol--A Prototyping Framework for Particle-Based Visualization

Visualization applications nowadays not only face increasingly larger datasets, but have to solve increasingly complex research questions. They often require more than a single algorithm and consequently a software solution will exceed the possibilities of simple research prototypes. Well-established systems intended for such complex visual analysis purposes have usually been designed for classical, mesh-based graphics approaches. For particle-based data, however, existing visualization frameworks are too generic - e.g. lacking possibilities for consistent low-level GPU optimization for high-performance graphics - and at the same time are too limited - e.g. by enforcing the use of structures suboptimal for some computations. Thus, we developed the system softwareMegaMol for visualization research on particle-based data. On the one hand, flexible data structures and functional module design allow for easy adaption to changing research questions, e.g. studying vapors in thermodynamics, solid material in physics, or complex functional macromolecules like proteins in biochemistry. Therefore, MegaMol is designed as a development framework. On the other hand, common functionality for data handling and advanced rendering implementations are available and beneficial for all applications. We present several case studies of work implemented using our system as well as a comparison to other freely available or open source systems.

Interactive visualization of APT data at full fidelity

Understanding the impact of noise and incomplete data is a critical need for using atom probe tomography effectively. Although many tools and techniques have been developed to address this problem, visualization of the raw data remains an important part of this process. In this paper, we present two contributions to the visualization of data acquired through atom probe tomography. First, we describe the application of a rendering technique, ray-cast spherical impostors, that enables the interactive rendering of large numbers (as large as 10 million plus) of pixel perfect, lit spheres representing individual atoms. This technique is made possible by the use of a consumer-level graphics processing unit (GPU), and it yields an order of magnitude improvement both in render quality and speed over techniques previously used to render spherical glyphs in this domain. Second, we present an interactive tool that allows the user to mask, filter, and colorize the data in real time to help them understand and visualize a precise subset and properties of the raw data. We demonstrate the effectiveness of our tool through benchmarks and an example that shows how the ability to interactively render large numbers of spheres, combined with the use of filters and masks, leads to improved understanding of the three-dimensional (3D) and incomplete nature of atom probe data. This improvement arises from the ability of lit spheres to more effectively show the 3D position and the local spatial distribution of individual atoms than what is possible with point or isosurface renderings. The techniques described in this paper serve to introduce new rendering and interaction techniques that have only recently become practical as well as new ways of interactively exploring the raw data.

Automated Illustration of Molecular Flexibility

In this paper, we present an approach to creating illustrations of molecular flexibility using normal mode analysis (NMA). The output of NMA is a collection of points corresponding to the locations of atoms and associated motion vectors, where a vector for each point is known. Our approach abstracts the complex object and its motion by grouping the points, models the motion of each group as an affine velocity, and depicts the motion of each group by automatically choosing glyphs such as arrows. Affine exponentials allow the extrapolation of nonlinear effects such as near rotations and spirals from the linear velocities. Our approach automatically groups points by finding sets of neighboring points whose motions fit the motion model. The geometry and motion models for each group are used to determine glyphs that depict the motion, with various aspects of the motion mapped to each glyph. We evaluated the utility of our system in real work done by structural biologists both by utilizing it in our own structural biology work and quantitatively measuring its usefulness on a set of known protein conformation changes. Additionally, in order to allow ourselves and our collaborators to effectively use our techniques we integrated our system with commonly used tools for molecular visualization.

GPU-accelerated atom and dynamic bond visualization using hyperballs: a unified algorithm for balls, sticks, and hyperboloids

Ray casting on graphics processing units (GPUs) opens new possibilities for molecular visualization. We describe the implementation and calculation of diverse molecular representations such as licorice, ball-and-stick, space-filling van der Waals spheres, and approximated solvent-accessible surfaces using GPUs. We introduce HyperBalls, an improved ball-and-stick representation replacing tubes, linking the atom spheres by hyperboloids that can smoothly connect them. This type of depiction is particularly useful to represent dynamic phenomena, such as the evolution of noncovalent bonds. It is furthermore well suited to represent coarse-grained models and spring networks. All these representations can be defined by a single general algebraic equation that is adapted for the ray-casting technique and is well suited for execution on the GPU. Using GPU capabilities, this implementation can routinely, accurately, and interactively render molecules ranging from a few atoms up to huge macromolecular assemblies with more than 500,000 particles. In simple cases, based only on spheres, we have been able to display up to two million atoms smoothly.

GPU-powered tools boost molecular visualization

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.

Interactive visualization of quantum-chemistry data

Simulation and computation in chemistry studies have improved as computational power has increased over recent decades. Many types of chemistry simulation results are available, from atomic level bonding to volumetric representations of electron density. However, tools for the visualization of the results from quantum-chemistry computations are still limited to showing atomic bonds and isosurfaces or isocontours corresponding to certain isovalues. In this work, we study the volumetric representations of the results from quantum-chemistry computations, and evaluate and visualize the representations directly on a modern graphics processing unit without resampling the result in grid structures. Our visualization tool handles the direct evaluation of the approximated wavefunctions described as a combination of Gaussian-like primitive basis functions. For visualizations, we use a slice-based volume-rendering technique with a two-dimensional transfer function, volume clipping and illustrative rendering in order to reveal and enhance the quantum-chemistry structure. Since there is no need to resample the volume from the functional representations for the volume rendering, two issues, data transfer and resampling resolution, can be ignored; therefore, it is possible to explore interactively a large amount of different information in the computation results.

Interactive volume rendering of functional representations in quantum chemistry

Simulation and computation in chemistry studies have been improved as computational power has increased over decades. Many types of chemistry simulation results are available, from atomic level bonding to volumetric representations of electron density. However, tools for the visualization of the results from quantum chemistry computations are still limited to showing atomic bonds and isosurfaces or isocontours corresponding to certain isovalues. In this work, we study the volumetric representations of the results from quantum chemistry computations, and evaluate and visualize the representations directly on the GPU without resampling the result in grid structures. Our visualization tool handles the direct evaluation of the approximated wavefunctions described as a combination of Gaussian-like primitive basis functions. For visualizations, we use a slice based volume rendering technique with a 2D transfer function, volume clipping, and illustrative rendering in order to reveal and enhance the quantum chemistry structure. Since there is no need of resampling the volume from the functional representations, two issues, data transfer and resampling resolution, can be ignored, therefore, it is possible to interactively explore large amount of different information in the computation results.