首页 | 本学科首页   官方微博 | 高级检索  
   检索      


A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology
Authors:Chou Kuo-Chen  Cai Yu-Dong
Institution:Gordon Life Science Institute, San Diego, CA 92130, USA. kchou@san.rr.com
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.
Keywords:Gene ontology  Functional domain composition  Pseudo-amino acid composition  InterPro database  Hybrid space  Intimate sorting algorithm  ISort predictor  Protein subcellular location
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号