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Applying machine learning strategies to scRNAseq datasets for the identification of genes associated with breast cancer recurrence.
The overarching goal of this project is to learn how to apply machine learning strategies to identify genes associated with breast cancer recurrence. The outcome of this project will be a working understanding of machine learning and its application for analyzing transcriptomic datasets. In addition, we will establish new collaborations with Dr. Sun Kim’s research team that will enable future exchange of trainees and innovations.
Faculty Supervisor:
Paola Marignani
Student:
Partner:
Seoul National University
Discipline:
Life Sciences
Sector:
Education
University:
Dalhousie University
Program:
Globalink Research Award
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.