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Translational bioinformatics in the cloud: an affordable alternative

by: Joel Dudley, Yannick Pouliot, Rong Chen, Alexander Morgan, Atul Butte
Genome Medicine, Vol. 2, No. 8. (2010), 51, doi:10.1186/gm172  Key: citeulike:7578650

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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.


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