Evaluation of Selected DNA Spectral Analysis-Based Gene Prediction Techniques

Title:Evaluation of Selected DNA Spectral Analysis-Based Gene Prediction Techniques

Volume: 12 Issue: 2

Author(s): Sajid A. Marhon and Stefan C. Kremer

Affiliation:

Keywords: DNA spectral analysis, discrete Fourier transform, period-3 property, gene finding, protein-coding region prediction.

Abstract: 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.

Cite this article as:

Marhon A. Sajid and Kremer C. Stefan, Evaluation of Selected DNA Spectral Analysis-Based Gene Prediction Techniques, Current Bioinformatics 2017; 12 (2) . https://dx.doi.org/10.2174/1574893610666151026214755