GKIN: a tool for drawing genetic networks

Abstract We present GKIN, a simulator and a comprehensive graphical interface where one can draw the model specification of reactions between hypothesized molecular participants in a gene regulatory and biochemical reaction network (or genetic network for short). The solver is written in C++ in a nearly platform independent manner to simulate large ensembles of models, which can run on PCs, Macintoshes, and UNIX machines, and its graphical user interface is written in Java which can run as a standalone or WebStart application. The drawing capability for rendering a network significantly enhances the ease of use of other reaction network simulators, such as KINSOLVE

Analysis of surface folding patterns of diccols using the GPU-Optimized geodesic field estimate

Localization of cortical regions of interests (ROIs) in the human brain via analysis of Diffusion Tensor Imaging (DTI) data plays a pivotal role in basic and clinical neuroscience. In recent studies, 358 common cortical landmarks in the human brain, termed as Dense Indi- vidualized and Common Connectivity-based Cortical Landmarks (DICCCOLs), have been identified. Each of these DICCCOL sites has been observed to possess fiber connection patterns that are consistent across individuals and populations and can be regarded as predictive of brain function. However, the regularity and variability of the cortical surface fold patterns at these DICCCOL sites have, thus far, not been investigated. This paper presents a novel approach, based on intrinsic surface geometry, for quantitative analysis of the regularity and variability of the cortical surface folding patterns with respect to the structural neural connectivity of the human brain. In particular, the Geodesic Field Estimate (GFE) is used to infer the relationship between the structural and connectional DTI features and the complex surface geometry of the human brain. A parallel algorithm, well suited for implementation on Graphics Processing Units (GPUs), is also proposed for efficient computation of the shortest geodesic paths between all cortical surface point pairs. Based on experimental results, a mathematical model for the morphological variability and regularity of the cortical folding patterns in the vicinity of the DICCCOL sites is proposed. It is envisioned that this model could be potentially applied in several human brain image registration and brain mapping applications

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(Under the Direction of Hamid Arabnia) The National Library of Medicine’s Visible Human Project is a digital image library containing full color anatomical, CT and MR images representing an adult male and female. Segmentation of the Visible Human datasets offers many additions to the original goal of a three-dimensional representation of a computer generated anatomical model of the human body. This paper presents an automatic segmentation algorithm called the Medical Image Segmentation Technique, MIST, which is based on a seeded region growing approach. The technique repeatedly extracts anatomical regions of interest from two-dimensional cross section images to create three-dimensional visualizations of these anatomical organs, bones and tissues. Resulting segmentations of this technique are compared with existing segmentation algorithms. This method proves to produce better whole organ and tissue segmentations than existing algorithms