Title |
Translational bioinformatics in the cloud: an affordable alternative
|
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Published in |
Genome Medicine, August 2010
|
DOI | 10.1186/gm172 |
Pubmed ID | |
Authors |
Joel T Dudley, Yannick Pouliot, Rong Chen, Alexander A Morgan, Atul J Butte |
Abstract |
With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 15 | 9% |
United Kingdom | 4 | 2% |
Brazil | 3 | 2% |
Netherlands | 3 | 2% |
France | 2 | 1% |
Korea, Republic of | 1 | <1% |
Finland | 1 | <1% |
New Zealand | 1 | <1% |
Argentina | 1 | <1% |
Other | 6 | 3% |
Unknown | 135 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 57 | 33% |
Student > Ph. D. Student | 28 | 16% |
Student > Master | 16 | 9% |
Other | 15 | 9% |
Professor | 11 | 6% |
Other | 33 | 19% |
Unknown | 12 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 72 | 42% |
Computer Science | 34 | 20% |
Medicine and Dentistry | 24 | 14% |
Biochemistry, Genetics and Molecular Biology | 10 | 6% |
Engineering | 6 | 3% |
Other | 12 | 7% |
Unknown | 14 | 8% |