| 利用支持向量机预测生物膜蛋白类型 |
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| 引用本文： | 郭宗明,张治洲,潘宇曦,黄振德,冯国鄞,贺林.利用支持向量机预测生物膜蛋白类型[J].上海交通大学学报,2004,38(5):806-809. |
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| 作者姓名： | 郭宗明 张治洲 潘宇曦 黄振德 冯国鄞 贺林 |
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| 作者单位： | 上海交通大学,Bio-X生命科学研究中心,上海,200030 |
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| 基金项目： | 教育部科学技术研究重点项目:蛋白组学新方法研究(03066) |
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| 摘 要： | 利用统计学习理论中的支持向量机(SVM)，基于氨基酸组分含量预测生物膜蛋白类型。使用文献中2059个训练集和2625个检验集膜蛋白序列数据，运用统计预测中的校准检验，留一法交叉检验和独立数据集检验方法进行分类预测。结果表明，SVM对膜蛋白类型预测具有明显的优越性，该算法对当前已有方法起到重要的补充作用。
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| 关 键 词： | 支持向量机 生物膜蛋白 氨基酸组分 |
| 文章编号： | 1006-2467(2004)05-0806-04 |
| 修稿时间： | 2003年3月31日 |
Prediction of Membrane Protein Types by Using Support Vector Machine |
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| GUO Zong-ming,ZHANG Zhi-zhou,PAN Yu-xi,HUANG Zhen-de,FENG Guo-yin,HE Lin.Prediction of Membrane Protein Types by Using Support Vector Machine[J].Journal of Shanghai Jiaotong University,2004,38(5):806-809. |
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| Authors: | GUO Zong-ming ZHANG Zhi-zhou PAN Yu-xi HUANG Zhen-de FENG Guo-yin HE Lin |
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| Abstract: | Support vector machine (SVM) based on statistical learning theory was applied for the classification of five membrane protein types by Self-consistency, Jackknife and Independent dataset test methods based on the training dataset of 2 059 membrane proteins and the test dataset of 2 625 membrane proteins derived from the article according to their amino acid compositions. The results obtained by the three typical test methods of statistical prediction field are quite promising, indicating the current approach can play a complemental role to the other existing methods for predicting the types of membrane proteins. |
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| Keywords: | support vector machine (SVM) membrane protein amino acid composition |
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