Embedded System of DNA Exon Predictor using Hidden Markov Model

Abstract

Philosophers have been trying to understand in any branches of Artificial Intelligence since thousand years ago. Al in Bioscience was born combined with Bioinformatic and produces many kinds of research areas especially in computational problem. Hidden Markov Model is a powerful statistical tool for describing an event within hidden states (unknown condition), such as predictor for exon section at Deoxyribonucleic Acid (DNA) sequence. Number of states, transition probabilities and emission distributional oribabilities are 3 major elements of HMM. Hidden Markov Model used Forward-Backward algorithm and Viterbi algorithm for implementing the HMM basic problems and solutions, includes evaluation, training and testing. Whereas, all this functions has been planted in Single Board Computer as the embedded platform. The reason of choosing SBC was influenced by Open Source Software (OSS) development area.