The recognition system of sickle cell anemia by using hidden markov model
International Journal of Development Research
The recognition system of sickle cell anemia by using hidden markov model
Received 14th May, 2017; Received in revised form 25th June, 2017; Accepted 22nd July, 2017; Published online 30th August, 2017
Copyright ©2017, Mohamed Soueycatt et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The study of genetic mutations, that is responsible for diseases , is an important issue in genetics for its close relationship with the genetic evolution of living organisms , In this paper we present an algorithm that is bases on the Hidden Markov Models of recognition to the mutation that causes one of the most common genetic diseases, Sickle Cell disease, thus diagnoses the person state (infected, uninfected) , This method is applied to DNA sequence , Deoxyribonucleic acid, the practical application shows that the rate of recognition of an infected person equals (99%) and the rate of recognition of a healthy person equals (86.33%) ,All the code is written by using statistical program R.
