PATTERN RECOGNITION METHODS FOR PREDICTING THE SECONDARY STRUCTURE OF PROTEINS
用模式识别方法预测蛋白质的二级结构

This paper describes a statistical pattern recognition method for predicting the secondary structure of proteins. The method is powerful but conceptually simple. In this approach, 5 properties of the 20 amino acids are used to map peptide sequences into a multivariate property space. The method can be performed by microcomputers or minicomputer, and the feature extraction and sample selection are considered to be the key points of this method. The experiment results show that the pattern recognition methods for predicting the secondary structure of proteins is a fair good method. But it still needs to be improved.