Predicting the genomic and phenotypic re-programming in organisms undergoing genetic perturbations is a challenging task in modern biology. It is hypothesized that genomic alterations perturb the dynamics of biological information flow. In the present study, a statistical data analysis framework was designed and the network entropy concept was employed to quantify the level of disorder at the transcriptional level as a result of the genomic re-programming of S. cerevisiae cells under genetic perturbations. The customized re-programming in transcription levels to different genetic modifications was observed and genetic mutations were characterized by enhanced network entropies, which revealed higher degree of randomness in mRNA expression levels. To our knowledge, this study constitutes the first numerical demonstration on the conservative energetic state of the microorganisms against genetic perturbations.