Modularity is the grouping of the components of a complex system into distinct units. Modular structure is pervasive in biology and has been especially studied in biological networks, including metabolic circuits, protein-protein interaction networks, ecological food webs, and human brain networks. However, beyond simply quantifying the organization of these different systems, modularity plays an important role in optimizing their functional capabilities. It affords a system greater evolvability, efficiency, and robustness to perturbation; however, depending on the function being carried out, lower modularity is sometimes more advantageous, as it does not constrain the system to a particular configuration. The interactions between system complexity, modularity, flexibility of module composition, task demand, and performance provide a versatile theoretical framework that can tackle a diverse set of problems. Under this generalized theoretical model, I have studied a broad range of biological systems: the CRISPR-Cas immune mechanism in bacteria, the human immune response to influenza, and the human brain both at rest and during task performance. This work has applications to increasing precision in genetic editing, improving flu vaccine selection and development, understanding music processing in the brain, and quantifying the cognitive health benefits of a therapeutic arts intervention.