Browsing by Author "Xie, Dawen"

Now showing 1 - 3 of 3
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    Dynamic Behavior Visualizer: A Dynamic Visual Analytics Framework for Understanding Complex Networked Models
    Maloo, Akshay (Virginia Tech, 2014-02-04)
    Dynamic Behavior Visualizer (DBV) is a visual analytics environment to visualize the spatial and temporal movements and behavioral changes of an individual or a group, e.g. family within a realistic urban environment. DBV is specifically designed to visualize the adaptive behavioral changes, as they pertain to the interactions with multiple inter-dependent infrastructures, in the aftermath of a large crisis, e.g. hurricane or the detonation of an improvised nuclear device. DBV is web-enabled and thus is easily accessible to any user with access to a web browser. A novel aspect of the system is its scale and fidelity. The goal of DBV is to synthesize information and derive insight from it; detect the expected and discover the unexpected; provide timely and easily understandable assessment and the ability to piece together all this information.
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    Effect of modelling slum populations on influenza spread in Delhi
    Chen, Jiangzhuo; Chu, Shuyu; Chungbaek, Youngyun; Khan, Maleq; Kuhlman, Christopher J.; Marathe, Achla; Mortveit, Henning; Vullikanti, Anil; Xie, Dawen (BMJ, 2016-01-01)
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    The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities
    Davis, James J.; Wattam, Alice R.; Aziz, Ramy K.; Brettin, Thomas; Butler, Ralph; Butler, Rory M.; Chlenski, Philippe; Conrad, Neal; Dickerman, Allan W.; Dietrich, Emily M.; Gabbard, Joseph L.; Gerdes, Svetlana; Guard, Andrew; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Murphy-Olson, Daniel E.; Nguyen, Marcus; Nordberg, Eric K.; Olsen, Gary J.; Olson, Robert D.; Overbeek, Jamie C.; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomas, Chris; VanOeffelen, Margo; Vonstein, Veronika; Warren, Andrew S.; Xia, Fangfang; Xie, Dawen; Yoo, Hyunseung; Stevens, Rick L. (2020-01-08)
    The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.