A population genetic model is used to describe dynamical aspects of chromosomal abberations observed in M-FISH experiments. Linear differential equations model the evolution of relative frequencies of mutations. The unknown parameters involved are estimated by maximum likelihood methods. We propose a scoring system to select the most important mutations. In order to reduce the number of parameters and computation time, only the highest ranked mutations are considered. First applications to M-FISH data show rather promising results.