Hidden Markov model for protein structural class prediction based on MATLAB / 国际生物医学工程杂志
International Journal of Biomedical Engineering
; (6): 350-352,372, 2012.
Article
in Zh
| WPRIM
| ID: wpr-598182
Responsible library:
WPRO
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.
Full text:
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Index:
WPRIM
Type of study:
Health_economic_evaluation
/
Prognostic_studies
Language:
Zh
Journal:
International Journal of Biomedical Engineering
Year:
2012
Type:
Article