Prediction of Protein Structural Class by Functional Link Artificial Neural Network Using Hybrid Feature Extraction Method

Abstract

During last few decades' accurate prediction of protein structural class has been a challenging problem. Efficient and meaningful representation of protein molecule plays a significant role. In this paper Chou's pseudo amino acid composition along with amphiphillic correlation factor and the spectral characteristics of the protein has been used to represent protein data. Thus a protein sample is represented by a set of discrete components which incorporate both the sequence order and the sequence length effects. On the basis of such a statistical framework a simple functionally linked artificial neural network has been used for structural class prediction.