Hidden Markov model for protein structural class prediction based on MATLAB
10.3760/cma.j.issn.1673-4181.2012.06.008
- VernacularTitle:基于MATLAB的隐马尔可夫模型预测蛋白质结构类
- Author:
Huiyun YANG
;
Ouyan SHI
;
Haixuan QIAO
;
Xin TIAN
- Publication Type:Journal Article
- Keywords:
Protein structural class;
Prediction;
Hidden Markov model;
3-state;
8-state
- From:
International Journal of Biomedical Engineering
2012;(6):350-352,372
- CountryChina
- Language:Chinese
-
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.
