| 基于特征综合的启动子识别方法 |
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| 引用本文： | 刘咏梅,董宜堃. 基于特征综合的启动子识别方法[J]. 计算机工程与应用, 2012, 48(11): 201-204 |
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| 作者姓名： | 刘咏梅 董宜堃 |
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| 作者单位： | 哈尔滨工程大学 计算机科学与技术学院，哈尔滨 150001 |
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| 基金项目： | 教育部留学回国人员科研启动基金资助项目; 中央高校基本科研业务费专项资金自由探索项目（No.HEUCF100604） |
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| 摘 要： | 针对真核生物启动子识别的高假阳性现状，提出了一种基于特征综合的真核启动子识别方法。通过提取人类启动子核苷酸联体统计信息作为特征，并使用主成分分析法进行主元提取。将10维主成分特征与2维CpG岛特征进行特征综合，共同作为BP神经网络的输入来识别启动子。对人类基因序列启动子的预测结果表明，不但有效地减小了假阳性，而且具有较好的敏感性和特异性。
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| 关 键 词： | 启动子 启动子识别 主成分分析 CpG岛 反向传播（BP）神经网络 |
Promoter recognition method based on integrated features |
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| LIU Yongmei , DONG Yikun. Promoter recognition method based on integrated features[J]. Computer Engineering and Applications, 2012, 48(11): 201-204 |
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| Authors: | LIU Yongmei DONG Yikun |
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| Affiliation: | College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China |
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| Abstract: | In order to improve the situation of high false positive in eukaryotic promoter recognition,a promoter predication method based on integrate-features is presented.The method employs human promoter codon and pentamer information as features,and extracts principal components by PCA.The 10-dimension features and 2-dimension CpG island information,based on integrated features,are put into the BP neural network as classifier.The experimental results show that the method not only reduces the false positives but also obtains a higher sensitivity and specificity. |
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| Keywords: | promoter promoter recognition principal component analysis CpG island Back Propagation（BP） neural network |
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