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Methods To Integrate Genetic And Clinical Data For Disease Subtyping, Diana Mabel Diaz-Herrera

Wayne State University Dissertations

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: Computational Approaches For Drug Repurposing And Cell Type Identification, Azam Peyvandipour

Wayne State University Dissertations

The traditional drug discovery process is extremely slow and costly. More than 90% of drugs fail to pass beyond the early stage of development and toxicity tests, and many of the drugs that go through early phases of the clinical trials fail because of adverse reactions, side effects, or lack of efficiency. In spite of unprecedented investments in research and development (R&D), the number of new FDA-approved drugs remains low, reflecting the limitations of the current R&D model.

In this context, finding new disease indications for existing drugs sidesteps these issues and can therefore increase the available therapeutic choices at …