Abstract
In this paper, we evaluated the complexity and accuracy of dicodon model for gene finding using Hidden Markov Model with Self-Identification Learning. We used five different models as competitors with smaller parametric space than the dicodon model. Our evaluation result shows that the dicodon model outperforms other competitors in terms of sensitivity as well as specificity. This result indicates that the dicodon model can not be represented by a combination of the pair amino-acid, the codon usage, and the G+C content.
