Transition State Analysis of HMM for DNA Exon Controlling Using Bioinformatic Simulation
Keywords:HMM, Transition state, Exon, Correlation Coefficient (CC)
This paper describes the analysis of transition state value of HMM for DNA exon controlling using Bioinformatic simulation. Exon region in DNA is called a coding sequence (CDS) of genes in many regions at least two regions of exon. HMM model is generate using start and stop gene as a state and consist of three bases in each states. Furthermore, the region of intron in the model is able to increase the states by separating bases GT and bases AG from the length of intron. HMM properties and parameters such as Markov chain, transition state, emission state, HMM training and HMM testing is used to identify original exon region with estimated exon. The performance of estimation result shown by Correlation Coefficient (CC). Random values of transition state used for HMM train makes many differences in the CC of the model. Furthermore, the analysis of transition state values is very important to finding optimum of CC. Several models with the parameters of HMM were simulated, trained and tested for the implementation of number of states with HMM method. The simulation result predicted that the CC value is very much influenced by the value of transition state and improved the number of states on the model makes increasing of CC.