| 蛋白质二级结构预测的人工神经网络方法研究 |
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| 引用本文： | 何琴,高建华,刘伟.蛋白质二级结构预测的人工神经网络方法研究[J].分析科学学报,2006,22(4):438-440. |
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| 作者姓名： | 何琴 高建华 刘伟 |
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| 作者单位： | 1. 郑州大学化学系
2. 郑州大学生物工程系,郑州,450052 |
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| 基金项目： | 河南省教育厅自然科学基金(No:9815007) |
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| 摘 要： | 本文比较了五种神经网络方法预测蛋白质二级结构的准确率,并做出初步评价。五种神经网络分别是:误差反传前向网络(BP),径向基函数网络(RBF),广义回归神经网络(GRNN),串并联叠层网络(CF),Elman网络(ELM)。结果显示:GRNN的预测准确率达85.7%,优于其它网络。本文还讨论了训练集样本数及参数的优化对GRNN预测准确率的影响。
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| 关 键 词： | 蛋白质 二级结构 神经网络 |
| 文章编号： | 1006-6144(2006)04-0438-03 |
| 收稿时间： | 2004-11-02 |
| 修稿时间： | 2004-12-29 |
Study of Neural Network Methods in Predicting Protein Secondary Structures |
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| HE Qin,GAO Jian-hua,LIU Wei.Study of Neural Network Methods in Predicting Protein Secondary Structures[J].Journal of Analytical Science,2006,22(4):438-440. |
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| Authors: | HE Qin GAO Jian-hua LIU Wei |
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| Institution: | 1. Department of Chemistry, Zhengzhou University ;2. Department of Biological Engineering ,Zhengzhou University ,Zhengzhou 450052 |
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| Abstract: | In this paper,five neural network models,such as back-propagation neural network(BPNN),radial basis neural network(RBFNN),generalized regression neural network(GRNN),cascade forward backpropagation neural network(CFNN) and Elman backpropagation neural network(ELMNN),have been evaluated in predicting protein secondary structures.The prediction accuracy of GRNN is better than the others.In addition,some affecting factors(the training sets and the parameters of network) are also discussed. |
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| Keywords: | Protein Secondary structure Neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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