In this paper, we modify a mathematical model for differential gene expression introduced by Eggenberger for simulating cell morphology in order to evolve aesthetic imagery from grids of cells. We focus upon investigating fitness criteria to use so that genetic learning can effectively guide the evolution of the underlying cellular processes that lead to aesthetic results. In the model, cellular processes are governed by regulatory genes and transcription factors in such a way that cells with identical genomes exhibit differences during development. By associating certain cell products with color channels, images obtained from grids consisting of only two types of interacting cells are shown to yield a rich generative framework for artistic exploration.