Protein Secondary Structure Prediction by Using PSSM Pseudo Digital Image of Proteins

Abstract

Protein secondary structure prediction is one of the hot topics of bioinformatics and computational biology. In this article we present a new method to predict secondary structure of proteins. PSSMs of proteins are used to generate pseudo image of proteins. These protein images are used to extract digital image features. Digital image features vectors used for similarity analysis. We believe that PSSM pseudo digital images of proteins could help us to represent protein global intrinsic information in order find globally similar proteins and use these similar proteins during prediction. Highest prediction accuracy for Q3 recorded as 72.1% by using the system. Beside the high accuracy, this method allows us to shorten computational time for predicting secondary structure of proteins.