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Protein Secondary Structure Prediction using Feed Forward Artificial Neural Network and Perceptron
Protein secondary structure prediction plays very important role in prediction of tertiary protein structure which in turn gives accurate information about its functions. In this work we have used Feed Forward and Perceptron Neural Network to predict protein secondary structure and also compare their performances. In this method an integer value is assigned to each amino acid and the data is normalized between 0 and 1. The data is trained with window size of 3 using MATLAB. This method gives high accuracy of prediction of protein secondary structure. In future we will try to incorporate physicochemical properties of the amino acids.
Feed Forward, Perceptron, Protein Secondary Structure.
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