Exon prediction on DNA-genes of Plasmodium falciparum based on coding sequence structure using hidden Markov model

Abstract

BACKGROUND A hidden Markov model (HMM) is used for exon prediction on DNA of genes Plasmodium falciparum that has a model structure based on exon region structure in coding sequence (CDS). The objective research was to develop a new structure model to predict exon on DNA-genes of Plasmodium falciparum based on CDS structure using the HMM system. METHODS Model design in CDS, between two exon regions can be found one intron region and the model state number is used for its region. Its state number is used by separating start codon from first exon region and stop codon from the last exon region up to 9. The Viterbi algorithm and the backward-forward method for transition as well as emission states are used for training process. Furthermore, Viterbi and Baum-Welch algorithms are used for the testing process. The correlation coefficient (CC) was used as performance indicator, as the ratio of the estimated state in the output and the original state in the input of the model. RESULTS The simulation results has shown that the CC values depend on the given of the backward-forward transition state values randomly. The model with state number 9 showed the highest average of CC values of 0.7289 for Viterbi algorithm, and is 0.7166 for Baum-Welch algorithm. However, the lowest average of CC values has been found for the model with state number five. Its values are 0.6735 by using Viterbi algorithm and 0.6661 by using Baum-Welch algorithm. CONCLUSION The new structure model based on HMM system was valid to predict exon on DNA-genes of Plasmodium falciparum.