title: A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology.
abstract: 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.
authors: Gordon Life Science Institute, San Diego, CA 92130, USA. kchou@san.rr.com
authors: Kuo-Chen
authors: KC
authors: Chou
authors: Yu-Dong
authors: YD
authors: Cai
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D005821:Genetic Techniques; D016678:Genome; D016680:Genome, Bacterial; D008962:Models, Theoretical; D009693:Nucleic Acid Hybridization; D017434:Protein Structure, Tertiary; D020543:Proteome; D020539:Sequence Analysis, Protein; D013347:Subcellular Fractions / Q000378:metabolism*
chemical_list: D020543:Proteome