|本期目录/Table of Contents|

[1]赵剑,许金涛,顾凌榕.蛋白质序列在频率域上的一种特征提取方法[J].南京工业大学学报(自然科学版),2013,35(06):113-119.[doi:10.3969/j.issn.1671-7627.2013.06.023]
 ZHAO Jian,XU Jingtao,GU Lingrong.Feature extraction method for protein sequences in the frequency domain[J].Journal of NANJING TECH UNIVERSITY(NATURAL SCIENCE EDITION),2013,35(06):113-119.[doi:10.3969/j.issn.1671-7627.2013.06.023]
点击复制

蛋白质序列在频率域上的一种特征提取方法()
分享到:

《南京工业大学学报(自然科学版)》[ISSN:1671-7627/CN:32-1670/N]

卷:
35
期数:
2013年06期
页码:
113-119
栏目:
出版日期:
2013-11-20

文章信息/Info

Title:
Feature extraction method for protein sequences in the frequency domain
文章编号:
1671-7627(2013)06-0113-07
作者:
赵剑12许金涛1顾凌榕1
1. 南京工业大学 理学院,江苏 南京 210009; 2. 南京工业大学 生物与制药工程学院,江苏 南京 210009
Author(s):
ZHAO Jian12XU Jingtao1GU Lingrong1
1. College of Sciences,Nanjing University of Technology,Nanjing 210009,China; 2. Biotechnology and Pharmaceutical Engineering,Nanjing University of Technology,Nanjing 210009,China
关键词:
氨基酸序列 互相关 自相关 特征提取 向量序列傅里叶变换 信噪比
Keywords:
amino acid sequence cross correlation auto-correlation feature extraction Fourier transform of vector sequences signal to noise ratio
分类号:
Q811.4
DOI:
10.3969/j.issn.1671-7627.2013.06.023
文献标志码:
A
摘要:
针对不同蛋白质选取不同的氨基酸指数进行蛋白质研究,提取氨基酸序列的位置和排列信息在频率上的特征频谱作为特征向量,通过计算特征向量的距离考察蛋白质的相似性。这是一种非比对相似性的判别方法。蛋白质组的聚类结果表明,蛋白质序列在频率域上的特征提取方法具有一定的应用价值和生物学意义。
Abstract:
Different amino acid indices were selected to investigate different proteins. The characteristic frequency spectrums corresponded to amino acid sequence-order information in the frequency domain were extracted as the feature vectors. By computing the distances of the vectors,it was valuable to evaluate the similarity of protein sequences. This was one of the alignment-free methods to recognize the homology. The clustering results of protein sequences showed that the feature extraction method had practical value and biology sense.

参考文献/References:

[1] 张振慧.蛋白质分类问题的特征提取算法研究[D].长沙:国防科学技术大学,2006.
[2] Nakashima H,Nishikawa K.Discrimination of intracellular and extracellular proteins using amino acid composition and residue-pair frequencies[J].Journal of Molecular Biology,1994,238(1):54-61.
[3] Luo R,Feng Z,Liu J.Prediction of protein structural class by amino acid and polypeptide composition [J].European Journal of Biochemistry,2002,269(17):4219-4225.
[4] Garg A,Bhasin M,Raghava G P S.Support vector machine-based method for subcellular localization of human proteins using amino acid compositions,their order,and similarity search [J].Journal of Biological Chemistry,2005,280(15):14427-14432.
[5] Bu W S,Feng Z P,Zhang Z,et al.Prediction of protein(domain)structural classes based on amino-acid index [J].European Journal of Biochemistry,1999,266(3):1043-1049.
[6] Chou K C.Pseudo amino acid composition and its applications in bioinformatics,proteomics and system biology[J].Current Proteomics,2009,6(4):262-274.
[7] Feng Z P,Zhang C T.A graphic representation of protein sequence and predicting the subcellular locations of prokaryotic proteins [J].The International Journal of Biochemistry & Cell Biology,2002,34(3):298-307.
[8] Metfessel B A,Connelly D P,Rich S S,et al.Cross-validation of protein structural class prediction using statistical clustering and neural networks[J].Protein Science,1993,2(7):1171-1182.
[9] Chou K C.Prediction of protein subcellular locations by incorporating quasi-sequence-order effect [J].Biochemical and Biophysical Research Communications,2000,278(2):477-483.
[10] Chou K C,Cai Y D.Predicting protein structural class by functional domain composition [J].Biochemical and Biophysical Research Communications,2004,321(4):1007-1009.
[11] Ashburner M,Ball C A,Blake J A,et al.Gene ontology:tool for the unification of biology [J].Nature Genetics,2000,25(1):25-29.
[12] Shen H B,Chou K C.PseAAC:a flexible web server for generating various kinds of protein pseudo amino acid composition [J].Analytical Biochemistry,2008,373(2):386-388.
[13] Nanni L,Lumini A.A new encoding technique for peptide classification [J].Expert Systems with Applications,2011,38(4):3185-3191.
[14] Liu H,Yang J,Wang M,et al.Using fourier spectrum analysis and pseudo amino acid composition for prediction of membrane protein types [J].The Protein Journal,2005,24(6):385-389.
[15] 赵剑,王嘉松,刘国庆.高维共鸣识别:蛋白质比较的新方法[J].计算机工程与应用,2013,49(9):224-228.
[16] 赵剑,许金涛.AAindex数据库中傅里叶方法的多重氨基酸指数选择[J].数据采集与处理,2013,28(5):643-649.
[17] Sims G E,Jun S R,Wu G A,et al.Alignment-free genome comparison with feature frequency profiles(FFP)and optimal resolutions [J].Proceedings of the National Academy of Sciences,2009,106(8):2677-2682.

备注/Memo

备注/Memo:
收稿日期:2013-07-25
基金项目:南京工业大学青年教师基金(44204117)
作者简介:赵剑(1975—),男,江苏兴化人,讲师,博士生,主要研究方向为信号处理和生物信息学,E-mail: zhaojian@njut.edu.cn..
更新日期/Last Update: 2013-11-30