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Protein Eight Secondary Structure Classes Prediction Using Artificial Neural Networks

Journal: International Journal of Genomics, Proteomics, Metabolomics & Bioinformatics (IJGPMB) (Vol.1, No. 4)

Publication Date:

Authors : ;

Page : 17-19

Keywords : Artificial Neural Networks; Bioinformatics; Machine Learning; Protein Secondary Structure Prediction.;

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Protein is considered the backbone of any human being. Protein is responsible for many functionalities in the human body, these functionalities differ according to the way protein amino acids (amino acids are the raw elements of protein) bond together. Then the protein forms its secondary,tertiary and quaternary structures from the amino acid structure (primary sequence) by forming hydrogen bonds. Many machine learning techniques have been used through the past decade to try to predict the protein secondary structure. The most commonly used paradigm was the Artificial Neural Networks. A lot of research was conducted in this field. This paper presents the usage of Artificial Neural Networks to predict the protein secondary structure. The difference this paper proposes is predicting the eight classes of secondary structure not only the three main classes named: alpha, beta and coil. The maximum accuracy reached is 71% which is better that other discussed methods.

Last modified: 2018-07-11 14:05:36