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When ASU’s Research Computing department embarked on building a data-intensive environment, they teamed up to design the system according to the well-defined needs of the university’s biomedical researchers. Through HDP, the team avoided complicated machine-to-machine interconnections and wired those interconnections into the distributed framework from the very beginning.
With HDP, ASU is able to have both the availability of data and the technical capability to analyze it. The university ASU researchers rapidly comb the terabytes of cancer data to perform efficient analysis.
The HDP cluster at Arizona State University has accumulated more than a petabyte of genomic data from multiple studies involving over 500 individuals in each study. Researchers in five different teams access this genomic data lake to investigate urgent cancer research questions such as:
• Why do some people develop cancer and other people don’t?
• Why do some people respond to particular therapies while others do not?
• How can we predict who should get particular therapies?
• How do we develop next-generation therapies for those who don’t respond to the existing ones?
Access to such a huge, rich dataset, combined with highly efficient computational power has transformed the kinds of questions that ASU researchers can ask.