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Health Informatics & Data Science awardees present their research to the Network

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On Thursday, February 19, recipients of 2024 and 2025 Health Informatics & Data Science Awards presented their research to Network members as part of the MOHCCN seminar series. 

This series provides a platform for trainees to share their research with the wider Network and beyond through short, plain-language presentations about how they're using Network-generated "big data" and disruptive technologies to advance cancer research and care.

This event was co-chaired by Sally Nystrom and Jennifer Coish, members of the MOHCCN Patient Working Group, and by Véronique LeBlanc, PhD, Network Program Manager and Scientific Writer, TFRI.

Watch the full video

Opening Remarks

Isabel Serrano, PhD - Managing Director, MOHCCN

Rapid-fire Talks

Characterizing the molecular and clinical landscape of BRAF-mutant colorectal cancer: toward the identification of novel therapeutic vulnerabilities

  • Emmanuelle Rousselle - PhD candidate, April Rose lab, McGill University

Plasma whole-genome sequencing to detect and characterize pancreatic ductal adenocarcinoma

  • Yuanchang Fang - (at the time of the award) PhD candidate, Faiyaz Notta lab, University of Toronto & Princess Margaret Cancer Centre

Decoding epithelial plasticity: Exploring the influence of SWI-SNF complex mutations on bladder cancer progression

  • Andrew Garven - PhD candidate, Amber Simpson lab, Queen's University

Evaluation of synthetic lethality in guiding cancer therapeutics

  • Julia Nguyen - PhD candidate, Benjamin Haibe-Kains lab, Department of Medical Biophysics, University of Toronto

Defining the genomic and immunologic landscape of colorectal cancer

  • Jorge Pinzón-Mejía - PhD candidate, Jeanette Boudreau lab, Dalhousie University

Using natural language processing to verify variant interpretation data in precision oncology

  • Caralyn Reisle - PhD candidate, Steven Jones lab, University of British Columbia & Canada's Michael Smith Genome Sciences Centre

DeepTumour: Using AI to identify tumour origin

  • Xindi Zhang - PhD candidate, Lincoln Stein lab, Department of Molecular Genetics, University of Toronto

MULTi-modal integration in pancreas cancer using machine Learning (MULTIPL): Personalized predictions of outcomes across the spectrum of disease and treatments

  • David Hénault - (at the time of the award) post-doctoral research fellow, Robert Grant lab, Princess Margaret Cancer Centre

Click here to view abstracts.

Marathon of Hope Cancer Centres Network Seminar Series: 

This series features virtual talks from MOHCCN research partner investigators and trainees. These seminars will be of interest primarily to cancer researchers, clinicians and trainees across the country. Learn about upcoming talks and watch past seminars.

 


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