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Affiliate Scientist, Princess Margaret Cancer Centre, University Health Network <<BR>> Research Associate, Donnelly Center for Cellular and Biomolecular Research, University of Toronto '''Education:''' Mohamed Ghadie completed his Ph.D. and Postdoctoral work in Biomedical Engineering with Prof. Yu (Brandon) Xia at !McGill University in Montreal, where he developed a multi-scale approach for in silico modelling of the cell by applying template-based methods to construct atomic-resolution structural models of nodes and edges in the human protein-protein interaction network ("interactome"). This multi-scale model of the cell enabled him to predict how the human interactome is perturbed by genetic mutations, and remodelled in different tissues and cell types through alternative splicing. Before that he completed his Masters degree in Electrical and Computer Engineering specializing in bioinformatics with Prof. Theodore Perkins at the Ottawa Hospital Research Institute, where he developed computational methods for analyzing high-throughput gene expression data in human blood stem cell differentiation. He completed his Bachelor in Electrical Engineering and Computing Technology at the University of Ottawa. '''Publications:''' * Ghadie M, and Xia Y (2021) Mutation edgotype drives fitness effect in human. Frontiers in Bioinformatics 1:690769. * Ghadie M, and Xia Y. (2019) Estimating dispensable content in the human interactome. Nature Communications 10(1), 3205. * Ghadie M, Coulombe-Huntington J, and Xia Y. (2018) Interactome evolution: insights from genome-wide analyses of protein–protein interactions. Current Opinion in Structural Biology 50, 42-48. * Ghadie M, Lambourne L, Vidal M, and Xia Y. (2017) Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing. PLOS Computational Biology 13(8), e1005717. * Ghadie M, Japkowicz N, and Perkins TJ. (2015) Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach. Bioinformatics 31(16), 2676-2682. '''Updates:''' [[/Intranet/Weekly|Weekly Updates]] |
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'''Updates:''' [[/Intranet/Weekly|Weekly Updates]] ... |
Mohamed Ghadie
Affiliate Scientist, Princess Margaret Cancer Centre, University Health Network
Research Associate, Donnelly Center for Cellular and Biomolecular Research, University of Toronto
Education:
Mohamed Ghadie completed his Ph.D. and Postdoctoral work in Biomedical Engineering with Prof. Yu (Brandon) Xia at McGill University in Montreal, where he developed a multi-scale approach for in silico modelling of the cell by applying template-based methods to construct atomic-resolution structural models of nodes and edges in the human protein-protein interaction network ("interactome"). This multi-scale model of the cell enabled him to predict how the human interactome is perturbed by genetic mutations, and remodelled in different tissues and cell types through alternative splicing. Before that he completed his Masters degree in Electrical and Computer Engineering specializing in bioinformatics with Prof. Theodore Perkins at the Ottawa Hospital Research Institute, where he developed computational methods for analyzing high-throughput gene expression data in human blood stem cell differentiation. He completed his Bachelor in Electrical Engineering and Computing Technology at the University of Ottawa.
Publications:
- Ghadie M, and Xia Y (2021) Mutation edgotype drives fitness effect in human. Frontiers in Bioinformatics 1:690769.
- Ghadie M, and Xia Y. (2019) Estimating dispensable content in the human interactome. Nature Communications 10(1), 3205.
- Ghadie M, Coulombe-Huntington J, and Xia Y. (2018) Interactome evolution: insights from genome-wide analyses of protein–protein interactions. Current Opinion in Structural Biology 50, 42-48.
- Ghadie M, Lambourne L, Vidal M, and Xia Y. (2017) Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing. PLOS Computational Biology 13(8), e1005717.
- Ghadie M, Japkowicz N, and Perkins TJ. (2015) Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach. Bioinformatics 31(16), 2676-2682.
Updates:
Contact:
Email: mohamed.ghadie *a-t* uhnresearch.ca