| 引用本文: | 管翠萍,石晶,徐惠娟.基于压缩氨基酸和支持向量机进行膜蛋白类型识别[J].生物信息学,2013,11(4):271-274. |
| GUAN Cui-ping,SHI Jing,XU Hui-juan.Prediction of membrane protein types based on compressed amino acids and support vector machine[J].Chinese Journal of Bioinformatics,2013,11(4):271-274. |
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| 摘要: |
| 膜蛋白是一类结构独特的蛋白质,是细胞执行各种功能的物质基础。根据其在细胞膜上的不同存在方式,主要分为六种类型。本文利用压缩的氨基酸对原始膜蛋白序列进行信息压缩,再对压缩序列进行氨基酸组成和顺序特征的提取,最后采用支持向量机构建分类模型。通过五叠交叉验证的结果表明,该方法对于六种膜蛋白的分类预测,准确度最高可达98％以上,平均预测准确度在85％以上,可有效实现膜蛋白六种类型的划分,为进一步分析膜蛋白的结构和功能奠定基础。 |
| 关键词: 膜蛋白 压缩氨基酸 支持向量机 |
| DOI：10.3969/j.issn.1672-5565.2013-04.20130405 |
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| Prediction of membrane protein types based on compressed amino acids and support vector machine |
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GUAN Cui-ping, SHI Jing, XU Hui-juan
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(Life science school, NingXia University, NingXia YinChuan 750021,China)
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| Abstract: |
| Membrane proteins which hold a particular structure are the exact substance in cells to implement various functions. Six types of membrane proteins were classified based on their different performances on cell membrane. In this study, compressed amino acids were used to compress the original membrance proteins sequences, and features in the form of single amino acid and dipeptide compositions were extracted from the compressed sequences. Finally, classifiers were developed using support vector machine (SVM). The results demonstrated that this method could well predict the types of membrane proteins as the accuracy rate of prediction is above 98％ and 85％ on average based on 5-fold cross-validation. This work will establish the basis for the further research of membrane protein’s structure and function. |
| Key words: Membrane Protein Compressed Amino Acids SVM |
