Using a commodity high-definition television for collaborative structural biology.

Visualization of protein structures using stereoscopic systems is frequently needed by structural biologists working to understand a protein's structure-function relationships. Often several scientists are working as a team and need simultaneous interaction with each other and the graphics representations. Most existing molecular visualization tools support single-user tasks, which are not suitable for a collaborative group. Expensive caves, domes or geowalls have been developed, but the availability and low cost of high-definition televisions (HDTVs) and game controllers in the commodity entertainment market provide an economically attractive option to achieve a collaborative environment. This paper describes a low-cost environment, using standard consumer game controllers and commercially available stereoscopic HDTV monitors with appropriate signal converters for structural biology collaborations employing existing binary distributions of commonly used software packages like Coot, PyMOL, Chimera, VMD, O, Olex2 and others.

Data mining for isotope discrimination in atom probe tomography.

Ions with similar time-of-flights (TOF) can be discriminated by mapping their kinetic energy. While current generation position-sensitive detectors have been considered insufficient for capturing the isotope kinetic energy, we demonstrate in this paper that statistical learning methodologies can be used to capture the kinetic energy from all of the parameters currently measured by mathematically transforming the signal. This approach works because the kinetic energy is sufficiently described by the descriptors on the potential, the material, and the evaporation process within atom probe tomography (APT). We discriminate the isotopes for Mg and Al by capturing the kinetic energy, and then decompose the TOF spectrum into its isotope components and identify the isotope for each individual atom measured. This work demonstrates the value of advanced data mining methods to help enhance the information resolution of the atom probe.

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.