Two major goals in the study of biological systems are inference and prediction. Inference creates a mathematical model of the datageneration process to formalize our understanding or test a hypothesis about how the system behaves. Prediction aims at forecasting unobserved outcomes or future behavior, such as whether a mouse with a given phenotype will have a disease. Prediction makes it possible to identify best courses of action (e.g. treatment choice) without requiring understanding of the underlying mechanisms. In a typical research project, both inference and prediction are of value— we want to know how biological processes work and what will happen next. For example, we might want to infer which biological processes are associated with the dysregulation of a gene in a disease as well as classify whether a subject has the disease and predict the best therapy, such as drug intervention or invasive surgery.