Optimizing period-3 methods for eukaryotic gene prediction

Abstract

In this paper, we firstly investigate the effect of window lengths on selected signal processing-based gene and exon prediction methods. We then optimize these methods to improve their prediction accuracy by employing the best DNA representation, a suitable window length, and boosting the output signals to enhance protein coding and suppress the non-coding regions. It is shown herein that the proposed method outperforms major existing time-domain, frequency- domain, and combined time-frequency approaches. By comparison with the existing DFT-based methods, the proposed method not only requires 50% less processing but also exhibits relative improvements of 53.3%, 46.7%, and 24.2% respectively over spectral content, spectral rotation, and paired and weighted spectral rotation measures in terms of prediction accuracy of exonic nucleotides at a 5% false positive rate using the GENSCAN test set.