Predicting the Secondary Structure of Proteins Using New Ways of Classification

In this paper we imitate the ways of the information theory and propose new ways to classify features from 20 amino acids, we then use the classify features as inputs code for a neural network and apply to prediction the secondary structure of globular protein and give a new thought to research the protein structure.