HFCAS OpenIR
Gray BP neural network based prediction of rice protein interaction network.
Wang X(王雪)
2018-01-05
发表期刊Cluster Computing
摘要
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 fifirstly. 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.
关键词Gray value BP neural network Rice protein interaction Prediction
学科门类工学::计算机科学与技术(可授工学、理学学位)
DOIdoi.org/10.1007/s10586-017-1663-0
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收录类别SCI
语种英语
引用统计
文献类型期刊论文
条目标识符http://ir.hfcas.ac.cn:8080/handle/334002/126103
专题中国科学院合肥物质科学研究院
作者单位Institute of Technical Biology & Agriculture Engineering, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Wang X. Gray BP neural network based prediction of rice protein interaction network.[J]. Cluster Computing,2018.
APA Wang X.(2018).Gray BP neural network based prediction of rice protein interaction network..Cluster Computing.
MLA Wang X."Gray BP neural network based prediction of rice protein interaction network.".Cluster Computing (2018).
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