Computational biologists aim to address fundamental and applied questions in biology and biomedicine, by analyzing and modeling biological datasets using sophisticated theoretical and computational techniques. They are engaged in the highly collaborative environment at QBI, both contributing to and benefiting from cutting-edge experimental technologies that generate large amounts of heterogeneous biological information.

Computational biologists often compute models of biological systems and processes, based on input information from varied experiments, physical theories, and statistical analyses. Examples include models of gene and protein networks, structural models of proteins and their complexes with other macromolecules and small molecules, as well as models of dynamic processes such as molecular transport through the cell membrane. These models are then used to rationalize existing data and make testable predictions, thus catalyzing the cycle of experiment and theory in biology and biomedicine. They also facilitate answering practical questions, such as what makes a particular virus strain more virulent than another; what molecular interactions are key to virulence; and how to disrupt these interactions with, for example, small molecules.