Abstract: In this era of big data, vast biomedical datasets, including genomic, transcriptomic, and clinical, are being generated daily. Thus, there is an increasing need to develop robust computational tools to analyze these datasets to extract biological value, whether understanding the spread of disease in populations or modeling complex cellular processes. At the pure-biology Wang Lab at the University of California, San Francisco, I will work with Principal Investigator Dr. Biao Wang to analyze lab-produced and public datasets to understand phosphorylation regulatory mechanisms, protein shuttling, and metabolic homeostasis. I will work to understand how specific protein sequences, called nuclear localization sequences (NLSs), are phosphorylated by kinases to regulate protein nucleocytoplasmic shuttling, i.e., the movement of proteins between the nucleus and cytoplasm. My project involves conducting an extensive literature review to understand pathways of nuclear import and export. It involves handling numerous classes of data, including protein sequence, phosphoproteomic, and annotation data, as well as corresponding genomic data. Understanding phosphorylation regulatory mechanisms can help us understand how protein sub-cellular localizations are impaired in disease.