SaaS Clouds Supporting Biology and Medicine - Cloud Computing with e-Science Applications - page 264

Using Uncinus, a case study was carried out that utilized personalized
genomics analysis to perform diagnosis of a patient's breast cancer tumor
to identify targeted drug treatment strategies. During this study, genomic
analysis tools were installed onto a cloud resource. This cloud resource was
then published, deployed, and exposed though Uncinus with minimal user
interaction. This case study clearly demonstrated how the automated pro-
cedures (proposed by the framework) allow biology and medical research-
ers to access and deploy cloud services. Through the cloud, researchers take
advantage of flexible pricing and on-demand resources that can provide
faster turnaround times on their experiments. In the case of embarrassingly
parallel applications, such as the presented personal genomics case study,
clouds can fully utilize scalability to analyze thousands of cancer genomes
at once (something not possible on HPC clusters).
A research cloud solution, like the one presented and implemented in
this chapter, allows biology and medical researchers to apply the power
of the cloud to their research. This solution was developed by abstracting
Amazon EC2 resources from application logic and identifying and automat-
ing common methods used in service deployment. In this way, SaaS clouds
can be developed that simplify the process of using HPC cloud computing
for research.
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