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We would like to thank the two anonymous reviewers for helpful suggestions and Dr. Peter Waddell for the use of computing resources, which were funded by R01LM8626 and used for the analysis of the C. elegans data.
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In this paper, we propose a software architecture-based approach for self-adaptive function that optimizes the use of computing resources by supporting dynamic re-deployment of software components.
This has led to considerable enthusiasm within the bioinformatics community for the use of cloud computing for NGS sequence analyses [ 10].
Such an amount of data represents the unique challenge for experiments and requires the extensive use of computing facilities all over the world.
This study serves as proof of concept for the use of GPU computing in automotive tasks.
The results obtained in this study can be considered as a proof of concept for the use of reservoir computing methods in the ICU.
This work was sponsored by the BiG Grid project for the use of the computing and storage facilities, with financial support from the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research, NWO).
In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services.
The use of cloud computing for medical research is still in the beginning stages, which means there's much more progress to be made.
We are continuing to evaluate and use the resulting tools and hope to thereby add to the growing body of experience with the use of cloud computing for research applications.
Other works focus on conceptual issues [17 19], hierarchical graphs [20], the use of grid computing for dynamic scalability in the cloud [21], and priority graphs [22], or the development of performance indices [23].
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