The Foundation made the difficult decision to end the Compute the Cure Cancer Research Grant program. Our 2017 grants will be the last awarded under this initiative.
As the amount of data available for discovery increases exponentially, unprecedented opportunity now exists for researchers to use computation to create new knowledge and a deeper understanding of the disease. Through our Compute the Cure research grants, we support projects that use innovative computing techniques to advance cancer research, diagnostics, and treatment.
Image courtesy of the National Cancer Institute.
Research teams from San Diego’s Ludwig Cancer Research Institute and the University of Toronto each received a $200,000 Compute the Cure grant from the NVIDIA Foundation. The institute’s group, led by Dr. Paul Mischel, is using high performance computing and GPU-accelerated deep learning to better understand the most potent “driver” genes and their role in cancer. Drs. Quaid Morris and David Duvenaud at the university will use deep learning and DNA sequencing data to rapidly build a cancer’s “family tree” — revealing the mutations that turn healthy cells into malignant tumors and enabling us to predict how they will evolve.
Anna Shcherbina, a Ph.D. student in the Department of Biomedical Informatics at Stanford University was awarded a Compute the Cure Graduate Fellowship grant for her research to develop deep learning algorithms that synergistically combine multiple types of genetic and epigenetic data to develop accurate models of gene regulation.
Research teams from the Translational Genomics Research Institute and University of North Texas each received $200,000 from the NVIDIA Foundation. The institute’s team is optimizing a GPU-accelerated statistical analysis tool to identify differences among groups of cells in the same tumor to move clinicians closer to precision medicine in cancer. The university’s team is using computational simulations to discover and characterize new cancer biomarkers to improve diagnostics and develop personalized genetic therapies.
Gang Wu, a Ph.D. student at the University of Sussex, was awarded a $25,000 Compute the Cure Graduate Fellowship grant for his research to enable interactive-rate fluorescence-lifetime imaging microscopy for improved cancer research, diagnosis, and treatment outcomes.
A research team at the University of Toronto, led by Dr. Brendan Frey, was awarded $200,000 to support its work using GPU-powered deep learning techniques to advance cancer diagnostics.
John Neylon, a Ph.D. student at UCLA, was awarded a $25,000 Compute the Cure Graduate Fellowship award for his research using GPUs to improve cancer treatments based on adaptive radiation therapy.
Research teams from the Dana-Farber Cancer Institute and Stanford University each received $200,000 from the NVIDIA Foundation. Led by Dr. John Quackenbush, the institute’s team is developing GPU-accelerated algorithms that can be used to discover cancer subtypes in large genomic mutational datasets. Dr. Vijay Pande’s team at the university is focused on using large-scale deep learning and simulation for personalized tumor diagnostics.
The NVIDIA Foundation awarded a $200,000 grant to Dr. Rommie Amaro, a researcher at the University of California, San Diego. Dr. Amaro is pursuing her work on a shareable GPU-accelerated workflow to help speed the development of drugs to fight cancer.
Learn more about our key strategies, focus areas, and diverse programs.