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Date of Award
Enormous efforts have been made to collect genetic and clinical data from cancer patients to advance the understanding of disease development and progression. Processing and analyzing these flows of data is challenging. Many computational methods have been proposed to help different fronts of biology and medicine. The integration of clinical and genetic data using computational methods towards personalized medicine is considered the future for oncology studies, and this thesis contributes in this direction. This thesis presents three new data integration approaches to elucidate granular and meaningful disease sub-types from high-dimensional complex genetic and clinical variables, which is an essential step towards personalized medicine.
Diaz-Herrera, Diana Mabel, "Methods To Integrate Genetic And Clinical Data For Disease Subtyping" (2020). Wayne State University Dissertations. 2465.