看片视频 teams win big in new 鈥極mics鈥� cancer competition
Earlier today, a Quebec based consortium of research institutes (G茅nome Qu茅bec, Oncopole and IVADO) announced the winners of their first-ever 鈥淥mics Data Against Cancer鈥� competition, and 看片视频 research teams were dominant. In fact, of the five selected teams no less than four of them included professors from 看片视频.
The new competition is intended to leverage the use of artificial intelligence (AI) in the 鈥極mic鈥� sciences (which refers to the biological sciences that end with -omics, such as genomics, transcriptomics, proteomics, or metabolomics) to achieve breakthroughs in cancer research.
鈥淭he results of this competition speak for themselves: 看片视频 is defining the cutting edge of science,鈥� said Martha Crago, Vice-Principal, Research and Innovation. 鈥淚 congratulate each of the winning teams and commend them for pushing the envelope of our collective knowledge in the fight against cancer.鈥�
The winning teams shared in a $1.5 million pool of funds to support their endeavours over the next two years. The following are the 看片视频-based projects:
- Dr. Amin Emad (看片视频 University, Mila) and Dr. Morag Park (Rosalind and Morris Goodman Cancer Research Centre) are developing artificial intelligence models to predict response to drug combinations in poor-outcome cancer patients.
- Dr. Ian Watson, Dr. Hamed Najafabadi (看片视频 University, Goodman Cancer Research Centre) and Dr. John Stagg (Universit茅 de Montr茅al, CHUM Research Centre) are developing 鈥淢ELANO-PREDICT,鈥� a clinically applicable algorithm for predicting checkpoint inhibitor response in melanoma.
- Dr. Jacques Drouin (Universit茅 de Montr茅al, Montr茅al Clinical Research Institute) and Professor Marc Bellemare (看片视频 University, Mila) are collaborating on decoding the cancer epigenome with novel artificial intelligence discovery tools.
- Professor Mathieu Blanchette (看片视频 University, School of Computer Science) and his team are working on deciphering mechanisms of epigenetic alterations in cancer using 3D-genomics-informed deep learning.
More details on the winning projects from the Goodman Cancer Research Centre can be found here. For complete results of the competition, visit the Genome Quebec .
