The immense growth in the volume of research literature and experimental data in the field of molecular biology calls for efficient automatic methods to capture and store information. In recent years, several groups have worked on specific problems in this area, such as automated selection of articles pertinent to molecular biology, or automated extraction of information using natural-language processing, information visualization, and generation of specialized knowledge bases for molecular biology. GeneWays is an integrated system that combines several such subtasks. It analyzes interactions between molecular substances, drawing on multiple sources of information to infer a consensus view of molecular networks. GeneWays is designed as an open platform, allowing researchers to query, review, and critique stored information.
The system described in this paper provides a real-time 3D visual experience by using an array of 64 video cameras and an integral photography display with 60 viewing directions. The live 3D scene in front of the camera array is reproduced by the full-color, full-parallax autostereoscopic display with interactive control of viewing parameters. The main technical challenge is fast and flexible conversion of the data from the 64 multicamera images to the integral photography format. Based on image-based rendering techniques, our conversion method first renders 60 novel images corresponding to the viewing directions of the display, and then arranges the rendered pixels to produce an integral photography image. For real-time processing on a single PC, all the conversion processes are implemented on a GPU with GPGPU techniques. The conversion method also allows a user to interactively control viewing parameters of the displayed image for reproducing the dynamic 3D scene with desirable parameters. This control is performed as a software process, without reconfiguring the hardware system, by changing the rendering parameters such as the convergence point of the rendering cameras and the interval between the viewpoints of the rendering cameras.
We introduce an ontological model for the representation of biological knowledge related to regulatory networks in vertebrates. We outline a taxonomy of the concepts, define their 'whole-to-part' relationships, describe the properties of major concepts, and outline a set of the most important axioms. The ontology is partially realized in a computer system designed to aid researchers in biology and medicine in visualizing and editing a representation of a signal transduction system.
To estimate the qualified viewing spaces for two-and multi-view autostereoscopic displays, the relationship between image quality (image comfort, annoying ghost image, depth perception) and various pairings between 3-D cross-talk in the left and right views are studied subjectively using a two-view autostereoscopic display and test charts for the left and right views with ghost images due to artificial 3-D cross-talk. The artificial 3-D cross-talk was tuned to simulate the view in the intermediate zone of the viewing spaces. It was shown that the stereoscopic images on a two-view autostereoscopic display cause discomfort when they are observed by the eye in the intermediate zone between the viewing spaces. This is because the ghost image due to large 3-D cross-talk in the intermediate zone elicits different depth perception from the depth induced by the original images for the left and right views, so the observer's depth perception is confused. Image comfort is also shown to be better for multi-views, especially the width of the viewing space, which is narrower than the interpupillary distance, where the parallax of the cross-talking image is small.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.