This article analyzes and evaluates several DNA spectral analysis-based gene prediction
techniques. This empirical review of this class of gene prediction techniques is beneficial to researchers
to evaluate the state of the art empirically and impartially in this study. The techniques are applied to
five benchmark datasets to evaluate and compare their performance. The receiver operating
characteristic (ROC) curves are plotted to compare the performance. In this work, we impartially
analyze the techniques by performing an empirical comparison and studying some issues that are
general obstacles in this class of techniques such as the tuning of the window length parameter and
signal thresholding. In addition, we analyze issues that are specific to certain techniques. The study
reveals that the window length parameter, signal thresholding, and noise are the main challenges of this
class of techniques that put their performance behind other non-DSP-based techniques; however, these
issues are underestimated by many researchers in the design of their techniques. Furthermore, the
analysis carried out in this study shows that the performance of the techniques is dependent on the
choice of the analyzed parameters. These parameters are different depending on the considered method.
The choice of the optimal value of these parameters is still an open research question.
Keywords: DNA spectral analysis, discrete Fourier transform, period-3 property, gene finding, protein-coding region
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