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Nearest neighbour algorithm for predicting protein subcellular location by combining functional domain composition and pseudo-amino acid composition

被引：103
作者：
Cai, YD
Chou, KC
机构：
[1] Chinese Acad Sci, Shanghai Res Ctr Biotechnol, Shanghai 200233, Peoples R China
[2] Pfizer Inc, Upjohn Labs, Kalamazoo, MI 49007 USA
来源：
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS | 2003年 / 305卷 / 02期
关键词：
hybrid algorithm; proteins subcellular location; functional domain composition; pseudo-amino acid composition; bioinformatics; proteomics;
D O I：
10.1016/S0006-291X(03)00775-7
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
In this paper, based on the approach by combining the "functional domain composition" [K.C. Chou, Y.D. Cai, J. Biol. Chem. 277 (2002) 45765] and the pseudo-amino acid composition [K.C. Chou, Proteins Struct. Funct. Genet. 43 (2001) 246; Correction Proteins Struct. Funct. Genet. 2044 (2001) 2060], the Nearest Neighbour Algorithm (NNA) was developed for predicting the protein subcellular location. Very high success rates were observed, suggesting that such a hybrid approach may become a useful high-throughput tool in the area of bioinformatics and proteomics. (C) 2003 Elsevier Science (USA). All rights reserved.
引用
收藏
页码：407 / 411
页数：5
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