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基于级联神经网络的蛋白质二级结构预测

Protein Secondary Structure Prediction Based on Cascade Neural Networks

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【Author】 WANG Yan-chun 1,2,HE Dong-jian 3,WANG Shou-zhi 4(1.College of Mechanical and Electronic Engineering,Northwest A&F University,Yangling 712100;2.College of Information Science and Engineering,Qingdao Agricultural University,Qingdao 266109;3.College of Information Engineering,Northwest A&F University,Yangling 712100;4.Department of Mechanical and Electronic Engineering,Weihai Vocational College,Weihai 264210)

【机构】西北农林科技大学机械与电子工程学院；青岛农业大学信息科学与工程学院；西北农林科技大学信息工程学院；威海职业学院机电工程系；

【摘要】为提高蛋白质二级结构预测的精度,提出一种由两层网络构成的级联神经网络模型。第1层网络采用具有差异度的5个子网构成的网络模型,对第2层网络的输入编码进行改进。对PDBSelect25中的36条蛋白质共6122个残基进行测试,结果表明,该模型能有效预测蛋白质二级结构,其预测精度分别比SNN,DSC,PREDSATOR方法提高5.31%,1.21%和0.92%,平均预测精度提高到69.61%。更多还原

【Abstract】 In order to improve the prediction accuracy of protein secondary structure,a cascade neural networks composed of two-level network is presented.The first level is composed of five subnets with different structure,and the coding method of the second-level is studied and improved. The model is employed to predict 36 nonhomologous protein sequences with 6 122 residues in PDBSelect25.Results show that the proposed model can efficiently improve the prediction accuracy,increasing the prediction accuracy by 5.31%,1.21%and 0.92%respectively compared with SNN,DSC and PREDSATOR method,improving the average prediction accuracy to 69.61%.更多还原

【关键词】神经网络；蛋白质；二级结构预测；
【Key words】 neural networks； protein； secondary structure prediction；

【基金】国家自然科学基金资助项目(30471138)

【文献出处】计算机工程 ,Computer Engineering , 编辑部邮箱 ,2010年04期

【分类号】TP183
【被引频次】13
【下载频次】248

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