Boolean networks are a mathematical model which has been widely used since decades in the context of biological regulation networks qualitative modelling. They consist in collections of entities, each having two possible local states (1 -- active, and 0 -- inactive), which interact with each other over discrete time. The simplicity of their setting together with their high abstraction level are especially convenient to focus on foundations of information transmission in genetic regulation, and on mathematical explanation and prediction of phenomenological observations. This chapter aims to present the Boolean modelling framework, by developing its theoretical bases and emphasizing its usefulness for capturing biological regulation phenomena. But it goes beyond that by covering their ability to capture the information transmission and its consequences depending on the ways the entities update their local state over time.