Gray BP neural network based prediction of rice protein interaction network
| Autor: | Ru Jing Wang, Xue Wang, Yuan Miao Gui, Yuan Yuan Wei, Yue Jin Wu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Artificial neural network
Computer Networks and Communications Computer science business.industry food and beverages 020206 networking & telecommunications Pattern recognition 02 engineering and technology Cross-validation Rice protein Interaction network 0202 electrical engineering electronic engineering information engineering Entropy (information theory) 020201 artificial intelligence & image processing Artificial intelligence business Software |
| Zdroj: | Cluster Computing. 22:4165-4171 |
| ISSN: | 1573-7543 1386-7857 |
| DOI: | 10.1007/s10586-017-1663-0 |
| Popis: | In order to improve the effectiveness of the network prediction result of rice protein interaction, the network prediction method of rice protein interaction based on gray BP neural network has been proposed. Firstly, a series of key features about interaction sites of rice protein such as the series spectrum, conserved weight, entropy value, accessible exterior product of compound and sequence rate, etc., should be extracted firstly. Then the gray BP neural network and their integration will be applied to the training and test of these sample set. Ten times of cross validation are applied to the training and test, and four groups of feature combinations of rice protein interaction with comparability are created. As for each time of the addition of new features in the experiment, the accurate prediction rate would be improved, especially in case of the addition of exterior product and sequence rate features, the accuracy can be improved greatly, which means that in case the combination of multiple features is adopted, the method of predicting the interaction of rice protein by combining the gray BP neural network algorithm is accurate and effective. |
| Databáze: | OpenAIRE |
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