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利用周氏伪氨基酸组成预测外膜蛋白的改进马氏判别法。

The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition.

作者信息

Lin Hao

机构信息

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.

出版信息

J Theor Biol. 2008 May 21;252(2):350-6. doi: 10.1016/j.jtbi.2008.02.004. Epub 2008 Feb 12.

Abstract

The outer membrane proteins (OMPs) are beta-barrel membrane proteins that performed lots of biology functions. The discriminating OMPs from other non-OMPs is a very important task for understanding some biochemical process. In this study, a method that combines increment of diversity with modified Mahalanobis Discriminant, called IDQD, is presented to predict 208 OMPs, 206 transmembrane helical proteins (TMHPs) and 673 globular proteins (GPs) by using Chou's pseudo amino acid compositions as parameters. The overall accuracy of jackknife cross-validation is 93.2% and 96.1%, respectively, for three datasets (OMPs, TMHPs and GPs) and two datasets (OMPs and non-OMPs). These predicted results suggest that the method can be effectively applied to discriminate OMPs, TMHPs and GPs. And it also indicates that the pseudo amino acid composition can better reflect the core feature of membrane proteins than the classical amino acid composition.

摘要

外膜蛋白(OMPs)是β-桶状膜蛋白,具有多种生物学功能。区分OMPs与其他非OMPs对于理解某些生化过程是一项非常重要的任务。在本研究中,提出了一种将多样性增量与改进的马氏判别相结合的方法,称为IDQD,通过使用周氏伪氨基酸组成作为参数来预测208个OMPs、206个跨膜螺旋蛋白(TMHPs)和673个球状蛋白(GPs)。对于三个数据集(OMPs、TMHPs和GPs)和两个数据集(OMPs和非OMPs),留一法交叉验证的总体准确率分别为93.2%和96.1%。这些预测结果表明该方法可有效应用于区分OMPs、TMHPs和GPs。这也表明伪氨基酸组成比经典氨基酸组成能更好地反映膜蛋白的核心特征。

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