The overall aim of our biological research is to supplement traditional experimental techniques with computational and engineering methodologies for gaining more insight into gene and protein interaction networks and gene expression dynamics. The following study demonstrates the effectiveness of using a signal processing technique called the Fast Fourier Transform (FFT) on time course microarray (TCM) data for finding genes whose expression oscillates over time.

Using FFT on previously published yeast TCM data, we find that 313 genes show periodic expression. Interestingly, there are four dominant periodicities,

one of which matches the yeast cell cycle. The biological processes underlying the remaining three periodicities remain unknown. Gene annotation and GO functional analysis verify the presence of periodic cell cycle genes within the set of 313 genes found. Thus, Fourier analysis is a valuable tool for understanding gene expression dynamics.