Protein Secondary Structure Prediction using Feed-Forward Neural Network

Abstract — Neural network is one of the successful methods for protein secondary structure prediction. Day to day this technology is modified, improved, even other methods also combined with it to get better result. In this paper we trained feed-forward neural network with proteins for secondary structure prediction. Using Java Object Oriented Neural Engine (JOONE) our achieved accuracy for helix prediction is 71 % and for sheet prediction is 65%. This paper is expected to benefit researchers in proteomics by presenting a summary of developments of neural network in this area. Index Terms — α-helix, β-sheet, bioinformatics, feed-forward neural network.