Chapter title |
A Cloud-Based Data Network Approach for Translational Cancer Research
|
---|---|
Chapter number | 16 |
Book title |
GeNeDis 2014
|
Published in |
Advances in experimental medicine and biology, January 2015
|
DOI | 10.1007/978-3-319-09012-2_16 |
Pubmed ID | |
Book ISBNs |
978-3-31-909011-5, 978-3-31-909012-2
|
Authors |
Wei Xing, Dimitrios Tsoumakos, Moustafa Ghanem, Xing, Wei, Tsoumakos, Dimitrios, Ghanem, Moustafa |
Abstract |
We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 8% |
Brazil | 1 | 8% |
Unknown | 10 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 3 | 25% |
Researcher | 2 | 17% |
Professor > Associate Professor | 2 | 17% |
Other | 1 | 8% |
Student > Master | 1 | 8% |
Other | 3 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 42% |
Medicine and Dentistry | 3 | 25% |
Agricultural and Biological Sciences | 2 | 17% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Unknown | 1 | 8% |