Modern biomedicine has generated unprecedented amounts of data, creating unique challenges in assimilating, organizing, analyzing, and interpreting these data. This talk will cover statistical and computational frameworks that acknowledge and exploit inherent complex structural relationships for both biomarker discovery and clinical prediction to aid translational medicine. The approaches will be illustrated using several case examples in oncology.