In the world of medicine, time matters ― particularly when you’re in a race to save lives. An algorithm developed by FIU researchers from the Knight Foundation School of Computing and Information Sciences (SCIS) could potentially shave weeks, or even months, off the time necessary to crunch large amounts of complicated data that scientists use to create new vaccines and medications, to develop better treatments for cancer and Alzheimer’s disease, and to make inroads in the area of personalized medicine. The algorithm may be used for research in other fields as well.
“Many of the instruments used by scientists have become more efficient in producing large data sets,” said Fahad Saeed, associate professor at SCIS. “But analyzing and processing the data has never been fast or efficient. We knew that if we could compress the data and share it across very large machines, we could speed up the process.”
Saeed and his graduate students and postdoctoral fellows have been working on harnessing the power of high-performance supercomputers for a decade. In 2020, The National Institutes of Health awarded a grant to FIU, with Saeed as the principal investigator. The goal was to develop an algorithm to help scientists who use mass spectrometry to study proteomics ― proteins in a cell, tissue or organism.
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