1. The technique used by the author (Grigorov, 2006) relies on singular-spectrum analysis (SSA). While the author has claimed to have used a nonlinear time series approach, SSA by very definition is a linear decomposition technique. The lag-correlation matrix constructed as a part of the SSA technique is a measure of linear correlation between the samples in the time series, hence representative of only linear statistical properties in the given time series. On a related note, SSA is used for non-parametric powerspectral estimation (Caratheodory and Fejer, 1911; Pisarenko, 1973; Sidiropoulos, 2001). Thus any claims nonlinear dynamical properties in the fruit-fly temporal gene expression profiles based on the results of SSA should be strongly discouraged. It is equally important to note that the concatenation procedure adopted in (Grigorov, 2006) does not necessarily constitute a time series analysis. A time series is basically discrete representation of a continuous signals sampled in amplitude and time. The sampling in turn can be uniform or non-uniform. The time axis fails to make sense if such time series are concatenated. In the present paradigm mere visualization of the gene expression profiles reveals that they share no apparent statistical similarities. Thus the concatenation procedure even if termed as a time series is likely to be non-stationary.