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Theoretical Study of Continuous B-Cell Epitopes with Developed BP Neural Network
College of Science, Jiamusi University, Jiamusi, China
College of Science, Jiamusi University, Jiamusi, China
College of Science, Hebei Polytechnic University, Tangshan, China · Department of Computer Science, University of Georgia, Georgia, USA
College of Science, Northeast Forestry University, Harbin, China
College of Science, Jiamusi University, Jiamusi, China
- 1 College of Science, Jiamusi University, Jiamusi, China
- 2 College of Science, Hebei Polytechnic University, Tangshan, China
- 3 Department of Computer Science, University of Georgia, Georgia, USA
- 4 College of Science, Northeast Forestry University, Harbin, China
Computational Chemistry·Volume 04, Issue 3·Pages 83–90·Published 2 June 2016·DOI10.4236/cc.2016.43008
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Abstract
In order to identify continuous B-cell epitopes effectively and to increase the success rate of experimental identification, the modified Back Propagation artificial neural network (BP neural network) was used to predict the continuous B-cell epitopes, and finally the predictive model for the B-cells epitopes was established. Comparing with the other predictive models, the prediction performance of this model is more excellent (AUC = 0.723). For the purpose of verifying the performance of the model, the prediction to the SWISS PROT NUMBER: P08677 was carried on, and the satisfying results were obtained.
KeywordsContinuous B-Cell EpitopesBP Neural NetworkTheory MethodPredictive Model
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