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Cao, Y., Liu, S., Zhang, L., Qin, J., Wang, J. and Tang, K. (2005) Prediction of Protein Structural Class with Rough Sets. Bmc Bioinformatics, 7, 1-6.

has been cited by the following article:

• TITLE: A GASVM Algorithm for Predicting Protein Structure Classes

  AUTHORS: Longlong Liu, Mingjiao Ma, Tingting Zhao

  KEYWORDS: Protein Structural Classes, Protein Secondary Structure, Genetic Algorithm, Support Vector Machine

  JOURNAL NAME: Journal of Computer and Communications, Vol.4 No.15, November 28, 2016

  ABSTRACT: The research methods of protein structure prediction mainly focus on finding effective features of protein sequences and developing suitable machine learning algorithms. But few people consider the importance of weights of features in classification. We propose the GASVM algorithm (classification accuracy of support vector machine is regarded as the fitness value of genetic algorithm) to optimize the coefficients of these 16 features (5 features are proposed first time) in the classification, and further develop a new feature vector. Finally, based on the new feature vector, this paper uses support vector machine and 10-fold cross-validation to classify the protein structure of 3 low similarity datasets (25PDB, 1189, FC699). Experimental results show that the overall classification accuracy of the new method is better than other methods.