Prediction of membrane protein types by means of wavelet analysis and cascaded neural networks

被引：48

作者：

Rezaei, Mohammad Ali ^{[1
]}

Abdolmaleki, Parviz ^{[1
]}

Karami, Zahra ^{[1
]}

Asadabadi, Ebrahim Barzegari ^{[1
]}

Sherafat, Mohammad Amin ^{[2
]}

Abrishami-Moghaddam, Hamid ^{[3
]}

Fadaie, Marziyeh ^{[1
]}

Forouzanfar, Mohammad ^{[3
]}

机构：

[1] Tarbiat Modares Univ, Fac Sci, Dept Biophys, Tehran, Iran

[2] Tarbiat Modares Univ, Sch Med, Dept Physiol, Tehran, Iran

[3] KN Toosi Univ Technol, Dept Elect Engn, Tehran, Iran

来源：

JOURNAL OF THEORETICAL BIOLOGY | 2008年 / 254卷 / 04期

关键词：

Discrete wavelet transform; Feature extraction; Hydropathy plot;

D O I：

10.1016/j.jtbi.2008.07.012

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In this study, membrane proteins were classified using the information hidden in their sequences. It was achieved by applying the wavelet analysis to the sequences and consequently extracting several features, each of them revealing a proportion of the information content present in the sequence. The resultant features were made normalized and subsequently fed into a cascaded model developed in order to reduce the effect of the existing bias in the dataset, rising from the difference in size of the membrane protein classes. The results indicate an improvement in prediction accuracy of the model in comparison with similar works. The application of the presented model can be extended to other fields of structural biology due to its efficiency, simplicity and flexibility. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：817 / 820

页数：4

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