Cloud Computing in Life Science Research

At the recent Molecular Medicine Tri-Conference (MMTC) in San Francisco*, an industry executive took me aside to ask: “Is Cloud computing ever going to take off?” The question frames an expectation that Cloud computing should be happening faster, but Cloud adoption depends on your definition of Cloud computing. If you consider the Cloud as “information-as-a-service,” then life sciences and biological research are indeed the early adopters.

Web portals such as NCBI Entrez, the UCSC Genome Browser, and EBI Ensemble carry a tremendous computational load for academic and industrial research. Despite large investments in private bio-portals, researchers often prefer public portals, because the information is more up to date and has better user interfaces . . .

End users don’t care where or how the information is computed and stored. A successful case study for Cloud computing is the Virtual Proteomics Data Analysis Cluster (ViPDAC) at the University of Wisconsin. The system runs protein identification both locally and remotely on Amazon servers, handling all data transfers, machine requisitioning and decommissioning, and parallelization operations for the end-users. This sounds exciting, so why aren’t all applications hosted in the Cloud? ...