| 蛋白质二级结构预测方法研究 |
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| 引用本文： | 王艳春.蛋白质二级结构预测方法研究[J].计算机工程与应用,2009,45(36):44-46. |
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| 作者姓名： | 王艳春 |
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| 作者单位： | 青岛农业大学,信息科学与工程学院,山东,青岛,266109;西北农林科技大学,机械与电子工程学院,陕西,杨陵,712100 |
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| 摘 要： | 为提高蛋白质二级结构预测精度,提出一种新的网络模型和编码方法。首先利用基因表达式编程(GEP)的全局搜索能力同时进化设计神经网络的结构和连接权;其次,对神经网络输入层编码进行了改进,添加了氨基酸残基所处的疏水环境。用PDB-Select25中的36条蛋白质共6122个残基进行测试,结果表明提出的网络模型和编码方法能有效提高蛋白质二级结构预测的精度。
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| 关 键 词： | 蛋白质 二级结构预测 基因表达式编程 神经网络 |
| 收稿时间： | 2009-1-4 |
| 修稿时间： | 2009-2-17
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Study of protein secondary structure prediction methods |
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| WANG Yan-chun.Study of protein secondary structure prediction methods[J].Computer Engineering and Applications,2009,45(36):44-46. |
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| Authors: | WANG Yan-chun |
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| Affiliation: | 1.College of Information Science and Engineering，Qingdao Agricultural University，Qingdao，Shandong 266109，China 2.College of Mechanical and Electronic Engineering，Northwest A &; F University，Yangling，Shaanxi 712100，China |
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| Abstract: | In order to improve the prediction accuracy of protein secondary structure，a new network model and its coding method are proposed.Firstly，the structure and connection weights of BP network are evolved simultaneously by using global research ability of GEP.Secondly，the coding method of neural network is improved by integrating the hydrophobic value around the residue.The model is employed to predict 36 nonhomologous protein sequences with 6，122 residues in PDBSelect25，the results show that the proposed model and coding method can efficiently improve the prediction accuracy. |
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| Keywords: | protein secondary structure prediction gene expression programming neural network |
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