The Gabuzda lab uses genetic, biochemical, metabolomic, systems biology, and computational approaches to study HIV infection and comorbidities including cancer. Research interests include understanding viral, host, and environmental factors that determine clinical outcomes, therapeutic responses, and accelerated aging. Current projects include studies on: 1) virus-host interactions during HIV replication and pathogenesis that impact immune control, inflammation, metabolic disorders, and comorbidities; 2) role of exosomes in cell-cell communication, immune regulation, stress responses, and disease pathophysiology; 3) mechanisms involved in HIV-associated neurological disorders and accelerated aging; 4) cancer risk and etiologies in aging populations with HIV. The lab is proficient at bioinformatic, computational, and systems biology approaches including generation, analysis, interpretation, and visualization of large data sets, big data handling, and using bioinformatic software and R programs for data integration, network prediction, pathway analysis, and modeling. The lab also uses machine learning and other computational approaches to model longitudinal trajectories and identify new predictors of clinical outcomes. The long-term goal is gaining multidisciplinary knowledge that leads to progress in personalized medicine for HIV-infected and aging populations.