Shariq Mohammed, a research fellow in Computational Medicine and Bioinformatics, will use models combining both imaging and genotypic data to study time-to-recurrence for gliomas. “We aim to integrate genetic susceptibility with tumor-imaging characteristics to determine time-to-recurrence in glioma patients,” says Shariq. He explains, “Gliomas are tumors that start in the glial cells of the brain or the spine and compose about 30% of all brain and central nervous system tumors, and 80% of all malignant brain tumors. We will build statistical models to predict post-treatment time-to-recurrence, an invaluable task which will not only guide physicians in making informed personalized treatment strategies but also shed light on the biological mechanisms underlying disease progression and outcomes. We aim to develop advanced analytic tools by leveraging Precision Health datasets to enable precision discovery, and potentially precision treatment. This project will involve collaboration with experts in Neuroradiology, Bioinformatics, and Biostatistics.”