In causally cohesive genotype–phenotype (cGP) models, the mapping from genotypes to phenotypes can be decomposed into two separate mappings. Mathematical models describing the dynamics of a biological system typically contain two types of elements, state variables that change with time and parameters that remain constant over the time scale of the study. This scheme applies to any level of biological resolution. A phenotype is any observable characteristic of interest, such as the trajectory of a state variable or a summary thereof. Because the parameters in a physiological model can be conceived as aggregated summaries of finer-scale underlying models, parameters are phenotypes too. In a causally cohesive multiscale model, this leads to layers of models. The mapping from genotypes to parameters can in principle be experimentally measured. With current technology this is in most cases a daunting task, but considerable insight can be obtained even if one does not have detailed information about this mapping.