| 利用BP神经网络预测蛋白质三级结构 |
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| 引用本文： | 蔡娜娜,陈月辉,李伟.利用BP神经网络预测蛋白质三级结构[J].济南大学学报(自然科学版),2009,23(4):331-333. |
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| 作者姓名： | 蔡娜娜 陈月辉 李伟 |
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| 作者单位： | 1. 济南大学,控制科学与工程学院,山东,济南,250022
2. 济南大学,信息科学与工程学院,山东,济南,250022 |
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| 基金项目： | 国家自然科学基金，山东省自然科学基金 |
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| 摘 要： | 在已知的蛋白质结构研究方法基础上,提出将多分类问题转化成一对多的二分类问题,来预测蛋白质的未知结构.训练多个单分类器进行分类;选用后向传播(Back Propagation, BP)神经网络作为分类预测模型;以伪氨基酸作为网络输入特征;选用Chou提出的蛋白质数据集;实验数据采用全交叉验证(Jackknife).结果表明:此法能够提高蛋白质三级结构预测的准确率.
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| 关 键 词： | 后向传播神经网络 伪氨基酸组成 全面交叉验证 |
Prediction of Protein Structural Class by BP Neural Network |
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| CAI Na-na,CHEN Yue-hui,LI Wei.Prediction of Protein Structural Class by BP Neural Network[J].Journal of Jinan University(Science & Technology),2009,23(4):331-333. |
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| Authors: | CAI Na-na CHEN Yue-hui LI Wei |
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| Institution: | a.School of Control Science and Engineering;b.School of Information Science and Engineering;University of Jinan;Jinan 250022;China |
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| Abstract: | Based on the known research method on protein structural class,a method of converting multi-classification problems into one to many two-category problems to predict unknown protein structure is presented.Training multiple single classifiers to classify the protein structural class,choosing back propagation neural network as the model of classifying and predicting the protein structural class,taking the feature of pseudo-amino acid(PseAA) composition as the input of the neural network,validating all experim... |
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| Keywords: | back propagation neural network pseudo-amino acid composition jackknife |
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