In this work, the dynamics of fluctuations in gene expression time series is investigated. By using collected data of gene expression from yeast and human organisms, we found that the fluctuations of gene expression level and its average value over time are strongly correlated and obey a scaling law. As this feature is found in yeast and human organisms, it suggests that probably this coupling is a common dynamical organizing property of all living systems. To understand these observations, we propose a stochastic model which can explain these collective fluctuations, and predict the scaling exponent. Interestingly, our results indicate that the observed scaling law emerges from the self-similarity symmetry embedded in gene expression fluctuations.
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