Abstract:
In this thesis, two models at different resolution levels are developed for the population dynamics of animal cell cultures at the mitotic stage. The first model is a biologically plausible cellular automata-like micro-model allowing distributed representation of the cell population in a flask, while the second one is a nonlinear type of macro-model based on a lumped representation of the total population and the total toxicity in the flask. As a specific application C2C12 cell cultures are studied. Experimental data have been gathered from such cultures, and used to tune the parameters of the micro-model. Similarly, the parameters of the macro-model have been tuned to the simulation results obtained from the micro-model. Comparison of the results show that the proposed micro-model is capable of representing the population dynamics at the mitotic stage with sufficient accuracy while the proposed macro-model can provide a good representation only under the assumptions that the flask is initially clean, and that the initial cell population is sufficiently large and uniformly distributed. Using experimental data of any cell culture, theoretically it should be possible to tune both models to represent the population dynamics of the respective cell culture. Another contribution of this theses beside the macro- and micro-models is a software tool which renders the process of cell counting easier and more accurate.