A mathematical model was developed which described the growth of yeast colonies based on the assumptions that (i) these populations were built up of single cells whose proliferation was (ii) exclusively controlled by nutrient availability in the environment. The model was of a hybrid cellular automaton type and described discrete cells residing on a one-dimensional lattice as well as on continuously distributed nutrients. Experimental results and numerical calculations were compared to elucidate under which cultivation conditions the diffusion-limited growth (DLG) was the major construction principle in yeast colonies. Simulations were scaled to the growth of Yarrowia lipolytica and Candida boidinii colonies under carbon and nitrogen limitation. They showed that nutrient-controlled growth of the individual cells resulted in DLG of the population. Quantitative predictions for the spatio-temporal development of the cell-density profile inside a growing yeast mycelium were compared to the growth characteristics of the model yeast mycelia. Only for the carbon-limited growth of C. boidinii colonies on glucose as the limiting nutrient resource did the DLG model reproduce the cell-density profile estimated at the end of the cultivation. Under all other cultivation conditions, strong discrepancies between calculations and experimental results were evident precluding DLG as the ruling regulatory mechanism. Thus, whether or not the development of a yeast population could be described by a DLG scenario, was strongly dependent on the particular cultivation conditions and the applied yeast species. In those cases for which the DLG hypothesis failed to explain the observed growth patterns, the underlying assumptions, i.e., the complete absence of nutrient translocation between the individual cells inside the yeast mycelia as well as the exclusively nutrient-controlled proliferation of the cells, have to be reevaluated. The presented study demonstrated how the mathematical analysis of growth processes in yeast populations could assist the experimental identification of potential regulatory mechanisms.