Secondary Structure Prediction of Protein Using Support Vector Machine and Neural Networks

ABSTRACT Bioinformatics is the science of managing, mining, and interpreting information from biological sequences and structures.Bioinformatics method are used to predict protein structure that mostly depends on the amino acid sequence. In computational biology the most important task is to solve the protein folding problem. To predict tertiary structure first we need to predict the secondary structure of protein.Secondary structure is intermediate part between primary and tertiary structureInorder to predict the secondary structure many methods are used i.e.Choufasman, Gor and machine learning techniques like Neural network and Support Vector Machine.In this paper, comparison of both Statistical technique SVM and NN is drawn. In this we compare the performance of neural network and support vector machine from predicting the secondary structure of protein from the protein structure is evaluated. For each NN and SVM, classifiers that will classify Alpha, Beta and Helix structure from the protein structure to distinguish between helices (H) strand (E), and coil (C).