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Julie Hussin

Julie Hussin

Appointment

Solution Network Member

Integrated AI for Health Imaging

Pan-Canadian AI Strategy

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About

Hussin is a researcher at the Montreal Heart Institute and a member of IVADO Data Science Institute, with the mandate of leveraging data science and machine learning (ML) techniques on molecular and clinical data to improve cardiovascular (CV) health in diverse populations. The prevention and management of CV disease requires combining multiple biological levels through flexible, fair, and interpretable computational strategies and her group’s work focuses on the development of ML approaches to analyze these data. They explore the potential of deep learning techniques in genomics, proposing a new deep learning architecture for omics data. They further develop deep neural network approaches for functional analysis of genes using sequences, co-expression patterns, and protein-protein interactions. They also use ML for metabolomics profiling of patients with myocardial infarction and heart failure, highlighting novel pathways of clinical interest. Finally, Hussin’s group developed ML algorithms to analyze SARS-CoV-2 genetic data and COVID19 outcomes.

Awards

  • Foundation of Stars Excellence Award in Pediatric research, Montréal, Canada (2011)
  • Human Frontiers Long-Term Postdoctoral Fellow (2013-2016)
  • Sponsored Young Researcher at the 64th Lindau Nobel Laureate Meeting (2014)
  • EPAC Fellowship, Linacre College, University of Oxford (2014-2017)
  • Recognition Bravo Recherche - Spécial COVID-19 (2021)

Relevant Publications

  • Romero A et al. 2017. Diet Networks: Thin Parameters for Fat Genomics. 5th International Conference on Learning Representations 2017. arXiv:1611.09340
  • Samman K, Mehanna P, et al. 2021. Ticagrelor differentially modulates Omega-3/6 Polyunsaturated Fatty Acids Levels compared to Clopidogrel in Patients with Myocardial Infarction. Cell Reports Medicine, 2, 1002999 https://doi.org/10.1016/j.xcrm.2021.100299
  • Hamelin D, Fournelle D, et al. 2021. The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA supertype-dependent manner. Cell Systems.
  • Pesaranghader A, Matwin S, et al. 2022. deepSimDEF: deep neural embeddings of gene products and Gene Ontology terms for functional analysis of genes. Bioinformatics
  • Kuchroo M, Huang J, et al. 2022. Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease. Nature Biotechnology

Institution

IVADO

Montréal Heart Institute

Université de Montréal

Education

  • Postdoctoral Fellow, University of Oxford (2016)
  • Ph.D. Bioinformatics, Université de Montréal, (2013)
  • M.Sc. Bioinformatics, Université de Montréal (2008)
  • B.Sc. Bioinformatics, Université de Montréal, Canada (2006)

Country

Canada

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