Identification of Exon-Intron Boundary by Hidden Markov Model and Evaluation with the Human Genome
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概要
- 論文の詳細を見る
Abstract It is important clarifying the function of the gene to extract exon, because exon is translated into the protein. In this laboratory has worked on the research of an automatic extraction of exon by using genetic programming (GP) and neural net work (NN). In this research, it has automatic of exon of human genome extracted it by using HMM as a comparison technique with these techniques. As a result, the identification accuracy of GT boundary became 90.7% and the identification accuracy in the AG boundary became 84.8%. Moreover, the comparison verification was done with HMM, GP, and NN.
- 宮崎大学の論文
著者
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Yoshihara Ikuo
Department Of Computer And Science And Systems Engineering Miyazaki University
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Yamamori Kunihito
Department Of Computer And Science And Systems Engineering Miyazaki University
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Arimura Kazuhiko
Graduate School of Engineering, University of Miyazaki
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Arimura Kazuhiko
Graduate School Of Engineering University Of Miyazaki
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