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Open Access Highly Accessed Correspondence

Translational bioinformatics in the cloud: an affordable alternative

Joel T Dudley123, Yannick Pouliot23, Rong Chen23, Alexander A Morgan123 and Atul J Butte23*

Author Affiliations

1 Program in Biomedical Informatics, Stanford University School of Medicine, 251 Campus Drive, Stanford, CA 94305, USA

2 Department of Pediatrics, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA

3 Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA 94304, USA

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Genome Medicine 2010, 2:51  doi:10.1186/gm172

Published: 6 August 2010


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.