Cloud Computing and Visualization Tools for KBase
It is becoming abundantly clear that the scientific world is being saturated by its own data, with raw data collection increasingly outpacing researchers ability to extract meaningful knowledge from it. Nowhere is this more apparent than in the proliferation of omics fields, which are generating staggering amounts of data. This proposal offers three distinct improvements for the Kbase community by (a) designing a new architecture for genetics algorithms to be incorporated in the cloud; (b) linking these algorithms to existing Kbase databases; and (c) integrating new visualization tools into Kbase. Our work in Phase I will investigate the design of these new components and demonstrate how they will work on a sampling of algorithms from Ohio State University (OSU). In Phase II and beyond, we envision a full-featured system that enables researchers to deploy and run their new algorithms in the cloud. Commercial Applications and Other Benefits: We expect researchers and corpora- tions alike to respond both to the draw of being able to use an openly available set of algorithms on-demand and to the benefits of incorporating their algorithms into a broader and more useable infrastructure. Genetics and systems biology laboratories at academic, government, and industrial research centers will desire the self-generating exposure to the community and new clients by building their own components for this system. This will clearly have a direct impact on the DOE Kbase community due to the direct links to Kbase algorithms and data. In addition to the public impact, the general market of software as a service (SaaS) is expanding rapidly and these tools will fit into this business model (see Commercialization Plan). Corporations can combine and organize these services as products to clients. Due to the open source nature of this code and the relatively low expense of cloud resources, these could be offered for free or at a very low cost. Corporations like Kitware that capitalize on collaborations will see economic benefits from working with new clients who desire to leverage and expand the platform.
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