Paradigms Joel Barker Pdf 2021 Download
Paradigms Joel Barker Pdf Download
As changing computing paradigms such as cloud computing become involved in managing the flood of sequencing data, privacy protection in the cloud environment becomes a major concern [ 47, 48 ]. Research in this field can broadly be split into two layers: first, sensitive data must be protected from leaking to a third party [ 49 ] and second, the cloud service provider should be made as oblivious as possible to the computation [ 50 ]. One possible culmination of these ideas could be the creation of a single, monolithic biomedical cloud that would contain all the protected data from genomics research projects. This would completely change the biomedical analysis ecosystem, with researchers gaining access to this single entry point and storing all their programs and analyses there. Smaller implementations of this strategy can be seen in the development of Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud resources, where datasets can be stored and shared on remote servers [ 48 ].
According to the scientific authors, there are three types of computational paradigms: problem-oriented, information-oriented, and analytic-oriented [ 48 ]. Each of these paradigms offers a unique set of tools that can be applied to solve specific problems. The data paradigm is determined by the different data acquisition methods used in the field. It can be static or dynamic. As sequencing data continues to grow, four approaches to storing it are being increasingly explored: federated storage, federated analysis, cloud infrastructure, and cloud analysis [ 49 ]. However, there is a paucity of mature tools for deploying such large-scale systems. It is an open problem in the genome informatics community to enable the efficient development and delivery of large-scale genomic data.
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