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FaST-LMM and Windows Azure Put Genetics Research on Faster Track Although researchers are able to collect, store, and analyze tremendous volumes of data, technological and storage limitations can severely impact the speed at which this data can be analyzed. A new algorithm developed by Microsoft Research, FaST-LMM, runs on Windows Azure in the cloud and expedites analysis time—reducing processing periods from years to just days or hours. An early application of FaST-LMM and Windows Azure helps researchers analyze data for the genetic causes of common diseases.

Business Needs The ability to store and analyze tremendous volumes of data is critical to researchers around the world. Although technological advances enable researchers to store and process ever-larger data stores, there are still challenges. CPU and storage limitations can hinder researchers, particularly those dealing with massive volumes of information, or “big data.” Scientists typically have used supercomputers to handle big data research, but CPU and storage limitations have restricted the potential speed and breadth of data processing that can be done at any given time. Microsoft Research has developed an alternative method for processing big data: the FaST-LMM (Factored Spectrally Transformed Linear Mixed Models) algorithm, which runs on Windows Azure.