| 蛋白亚细胞定位的预测方法研究 |
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| 引用本文： | 王明会,李骜,谢丹,冯焕清. 蛋白亚细胞定位的预测方法研究[J]. 北京生物医学工程, 2006, 25(6): 649-653,657 |
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| 作者姓名： | 王明会 李骜 谢丹 冯焕清 |
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| 作者单位： | 中国科学技术大学电子科技系,合肥,230026;中国科学技术大学电子科技系,合肥,230026;中国科学技术大学电子科技系,合肥,230026;中国科学技术大学电子科技系,合肥,230026 |
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| 基金项目： | 中国科学技术大学校科研和教改项目 |
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| 摘 要： | 预测蛋白质的亚细胞定位信息对于了解其功能有重要的意义.选择氨基酸组成、氨基酸对组成、位置特异性打分矩阵三种分类特征以及模糊k近邻、支持向量机两种预测方法,分别进行了测试.对预测结果的分析显示,位置特异性打分矩阵可以提高对不同亚细胞器的可区分性;而支持向量机可以更好地利用位置特刎异性打分矩阵特征进行预测.使用氨基酸组成和位置特异性打分矩阵两种特征,并结合支持向量机,是一种有效的亚细胞定位预测方法.
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| 关 键 词： | 亚细胞定位 位置特异性打分矩阵 模糊k近邻 支持向量机 生物信息学 |
| 文章编号： | 1002-3208（2006）06-0649-05 |
| 收稿时间： | 2005-10-31 |
| 修稿时间： | 2005-10-31 |
A Study of Prediction Methods for Protein Subcellular Localization |
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| WANG Minghui,LI Ao,XIE Dan,FENG Huanqing. A Study of Prediction Methods for Protein Subcellular Localization[J]. Beijing Biomedical Engineering, 2006, 25(6): 649-653,657 |
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| Authors: | WANG Minghui LI Ao XIE Dan FENG Huanqing |
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| Affiliation: | Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230026 |
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| Abstract: | Prediction of protein subcellular location is one of the key functional characters to understand its biological function.Totally three kinds of input features were investigated in this paper,i.e.,amino acid composition,amino acid pair composition and position-specific scoring matrix(PSSM).In addition,the fuzzy k-NN and support vector machine(SVM)were employed which are more suitable for this purpose.Comprehensive comparison of prediction results on several data sets shows that PSSM is better than the other two features.SVM,a novel machine learning based on statistical learning theory,can make better use of PSSM than fuzzy k-NN method.Finally,the best prediction performance can be achieved by adopting both PSSM and amino acid composition as input feature and SVM for prediction. |
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| Keywords: | Subcellular localization position specific scoring matrix fuzzy k-NN support vector machine bioinformatics |
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