Hidden Markov model for protein structural class prediction based on MATLAB / 国际生物医学工程杂志

ABSTRACT

Objective Predicting protein structural class is the basis for predicting protein spatial structure,so it is important to improve the prediction accuracy of protein structural class.Methods We proposed 3-state and 8-state Hidden Markov model (HMM),and applied these HMMs to the prediction of protein structural class,respectively.We evaluated their accuracy on two different datasets through the rigorous jackknife cross-validation test.Results Prediction ability of 8-state HMM and 3-state HMM to all α class were excellent,the prediction accuracy of 3-state HMM even reached above 95％.Compared with Chou data set,the prediction accuracy of Zhou data set for all β class and α/β class of was improved,while overall prediction accuracy increased by 2％.Conclusion HMM is an effective method to predict protein structural class.