Transmembrane helix prediction using feed-forward neural network

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 trans-membrane protein for helix prediction. Using Java object oriented neural engine (JOONE) our achieved accuracy is 71%. This paper is expected to benefit researchers in proteomics by presenting a summary of developments of neural network in this area.