Title |
An interactive web application for the dissemination of human systems immunology data
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Published in |
Journal of Translational Medicine, June 2015
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DOI | 10.1186/s12967-015-0541-x |
Pubmed ID | |
Authors |
Cate Speake, Scott Presnell, Kelly Domico, Brad Zeitner, Anna Bjork, David Anderson, Michael J. Mason, Elizabeth Whalen, Olivia Vargas, Dimitry Popov, Darawan Rinchai, Noemie Jourde-Chiche, Laurent Chiche, Charlie Quinn, Damien Chaussabel |
Abstract |
Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators' interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery. State of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples. We provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page ( https://gxb.benaroyaresearch.org/dm3/landing.gsp )]. The source code is also available openly [Gene Expression Browser Source Code ( https://github.com/BenaroyaResearch/gxbrowser )]. We have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
United States | 1 | 2% |
France | 1 | 2% |
Australia | 1 | 2% |
Unknown | 43 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 23% |
Researcher | 10 | 21% |
Student > Master | 6 | 13% |
Student > Bachelor | 5 | 11% |
Professor | 3 | 6% |
Other | 5 | 11% |
Unknown | 7 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 11 | 23% |
Computer Science | 8 | 17% |
Biochemistry, Genetics and Molecular Biology | 7 | 15% |
Medicine and Dentistry | 6 | 13% |
Immunology and Microbiology | 2 | 4% |
Other | 5 | 11% |
Unknown | 8 | 17% |