About
Michael Ho is a Sessional Lecturer II in the Department of Economics at the University of Toronto. His academic role focuses on teaching, with affiliations in the broader academic community. Despite his teaching position, his research interests and publications reflect interdisciplinary work in genomics, epigenetics, and computational biology.
His research explores advanced topics such as epigenetic mechanisms in stem cells, cancer biomarker discovery, and clinical prediction models. Notable areas include the application of machine learning to genomic data analysis, validation frameworks for bioinformatics methods, and translational research in prenatal diagnostics and oncology.
Recent work emphasizes the integration of chromatin dynamics, DNA methylation profiling, and AI-driven approaches to solve challenges in personalized medicine. His contributions span both foundational genomic studies and applied research in healthcare technology.
Mr. Ho has actively participated in international collaborations, including guideline development for clinical prediction models (TRIPOD+ AI) and standards for genomic data interoperability (e.g., BED format). His publications highlight a commitment to methodological rigor in computational biology and translational genomics.
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