A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology

被引:133
作者
Chou, KC [1 ]
Cai, YD
机构
[1] Gordon Life Sci Inst, San Diego, CA 92130 USA
[2] TIBDD, Tianjin, Peoples R China
[3] UMIST, Biomol Sci Dept, Manchester M60 1QD, Lancs, England
关键词
gene ontology; functional domain composition; pseudo-amino acid composition; InterPro database; hybrid space; intimate sorting algorithm; ISort predictor; protein subcellular location;
D O I
10.1016/j.bbrc.2003.10.062
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
Based on the recent development in the gene ontology and functional domain databases, a new hybridization approach is developed for predicting protein subcellular location by combining the gene product, functional domain, and quasi-sequence-order effects. As a showcase, the same prokaryotic and eukaryotic datasets, which were studied by many previous investigators, are used for demonstration. The overall success rate by the jackknife test for the prokaryotic set is 94.7% and that for the eukaryotic set 92.9%. These are so far the highest success rates achieved for the two datasets by following a rigorous cross-validation test procedure, suggesting that such a hybrid approach may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology. The very high success rates also reflect the fact that the subcellular localization of a protein is closely correlated with: (1) the biological objective to which the gene or gene product contributes, (2) the biochemical activity of a gene product, and (3) the place in the cell where a gene product is active. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:743 / 747
页数:5
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