Prediction of Hemoglobin Structure from DNA Sequence through Neural Network and Hidden Markov Model

被引：0
|
作者：
Mubark, R. I. [1 ]
Keshk, H. A. [1 ]
Eladawy, M. I. [1 ]
机构：
[1] Helwan Univ, Elect Commun & Comp Engn Dept, Helwan, Egypt
来源：
PROCEEDINGS OF THE 7TH WSEAS INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, MAN-MACHINE SYSTEMS AND CYBERNETICS (CIMMACS '08): RECENT ADVANCES IN COMPUTATIONAL INTELLIGENCE, MAN-MACHINE SYSTEMS AND CYBERNETICS | 2008年
关键词：
Bioinformatics; Genetic sequences; Hemoglobin; Protein prediction; Neural network; Hidden markov model; Classification algorithm;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
One of the greatest challenges today in bioinformatics is to predict the structure of the protein from the DNA sequence. Protein structural domains are often associated with a particular protein function also the structure contains a valuable information to the biologists instead of the meaningless sequence. Because the experimental techniques that used to determine protein structure such as the x-ray crystallography and Nuclear Magnetic Resonance "NMR" spectroscopy are very expensive and can not be applied all the time, so the prediction may be the way to get the protein structure. In this work we will be able to predict the 3D structure of hemoglobin using two techniques; the neural network and hidden Markov model. Also, the prediction of the secondary structure is applied using multiple alignments.
引用
收藏
页码：65 / 70
页数：6
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