Hybrid Model of Neural Network and Hidden Markov Model for Protein Secondary Structure Prediction

机译：神经网络和隐马尔可夫模型的混合蛋白质二级结构预测

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Protein secondary structure prediction is an important step towards understanding how proteins fold in three dimensions. Using multiple sequence alignments, two layers NN-based method gets higher prediction accuracy. But window-based approach in NN-based method has the disadvantage of only considering the local information. Recent analysis by information theory indicates that the correlation between neighboring secondary structures are much stronger than that of neighboring amino acids. So we use a 7-state HMM to replace the second layer network. 496 proteins selected from the dataset CB513 are used in a 7-fold cross validation. The hybrid model appears to be very efficient, with Q3 score of 75.96% and SOV of 71.27%, more than 0.96% and 0.45% above two layers NN-based method. This hybrid model not only captures the local information, but considers the long-distance information. So it can get higher prediction accuracy.

机译：蛋白质二级结构预测是迈向了解蛋白质如何在三个维度上折叠的重要一步。使用多个序列比对，基于神经网络的两层方法可获得更高的预测精度。但是基于窗口的方法在基于NN的方法中具有仅考虑本地信息的缺点。信息理论的最新分析表明，相邻二级结构之间的相关性比相邻氨基酸之间的相关性强得多。因此，我们使用7状态HMM来替换第二层网络。从数据集CB513中选择的496种蛋白质被用于7倍交叉验证中。混合模型似乎非常有效，Q3得分为75.96％，SOV为71.27％，比基于NN的两层方法高出0.96％和0.45％。这种混合模型不仅捕获本地信息，而且考虑长途信息。这样可以获得更高的预测精度。

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来源
《International Forum on Progress on Post-Genome Technologies(5'IFPT); 20070910-11; Suzhou(CN)》|2007年|P.1-5|共5页
会议地点 Suzhou(CN)
作者
Ou-Yan Shi; Hui-Yun Yang; Jing Yang; Xin Tian;
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作者单位

Department of Biomedical Engineering, Tianjin Medical University, Tianjin 300070,China;

College of Basic Medicine,Tianjin Medical University,Tianjin 300070,China;

Department of Biomedical Engineering, Tianjin Medical University, Tianjin 300070,China;

Colleg;

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原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;
关键词
protein secondary structure prediction; hidden markov model; artificial neural network;

机译：蛋白质二级结构预测；隐马尔可夫模型；人工神经网络;

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4. Hybrid Model of Neural Network and Hidden Markov Model for Protein Secondary Structure Prediction [C] . Ou-Yan Shi, College of Basic Medicine, Hui-Yun Yang, . 2007

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Hybrid Model of Neural Network and Hidden Markov Model for Protein Secondary Structure Prediction

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