Prediction of functional modules based on comparative genome analysis and Gene Ontology application.

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by Hongwei Wu, Zhengchang Su, Fenglou Mao, Victor Olman, Ying Xu
Abstract:
We present a computational method for the prediction of functional modules encoded in microbial genomes. In this work, we have also developed a formal measure to quantify the degree of consistency between the predicted and the known modules, and have carried out statistical significance analysis of consistency measures. We first evaluate the functional relationship between two genes from three different perspectives--phylogenetic profile analysis, gene neighborhood analysis and Gene Ontology assignments. We then combine the three different sources of information in the framework of Bayesian inference, and we use the combined information to measure the strength of gene functional relationship. Finally, we apply a threshold-based method to predict functional modules. By applying this method to Escherichia coli K12, we have predicted 185 functional modules. Our predictions are highly consistent with the previously known functional modules in E.coli. The application results have demonstrated that our approach is highly promising for the prediction of functional modules encoded in a microbial genome.
Reference:
Prediction of functional modules based on comparative genome analysis and Gene Ontology application. (Hongwei Wu, Zhengchang Su, Fenglou Mao, Victor Olman, Ying Xu), In Nucleic acids research, volume 33, 2005.
Bibtex Entry:
@article{Wu2005,
abstract = {We present a computational method for the prediction of functional modules encoded in microbial genomes. In this work, we have also developed a formal measure to quantify the degree of consistency between the predicted and the known modules, and have carried out statistical significance analysis of consistency measures. We first evaluate the functional relationship between two genes from three different perspectives--phylogenetic profile analysis, gene neighborhood analysis and Gene Ontology assignments. We then combine the three different sources of information in the framework of Bayesian inference, and we use the combined information to measure the strength of gene functional relationship. Finally, we apply a threshold-based method to predict functional modules. By applying this method to Escherichia coli K12, we have predicted 185 functional modules. Our predictions are highly consistent with the previously known functional modules in E.coli. The application results have demonstrated that our approach is highly promising for the prediction of functional modules encoded in a microbial genome.},
author = {Wu, Hongwei and Su, Zhengchang and Mao, Fenglou and Olman, Victor and Xu, Ying},
doi = {10.1093/nar/gki573},
issn = {1362-4962},
journal = {Nucleic acids research},
keywords = {Bacterial,Bayes Theorem,Computational Biology,Computational Biology: methods,Data Interpretation,Escherichia coli,Escherichia coli: genetics,GO sim,Genome,Genomics,Genomics: methods,Phylogeny,Reproducibility of Results,SML-LIB-BIBLIO,Semantic Similarity,Statistical,lang:ENG,semantic similarity},
mendeley-tags = {GO sim,SML-LIB-BIBLIO,lang:ENG,semantic similarity},
month = jan,
number = {9},
pages = {2822--37},
pmid = {15901854},
title = {{Prediction of functional modules based on comparative genome analysis and Gene Ontology application.}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1130488\&tool=pmcentrez\&rendertype=abstract},
volume = {33},
year = {2005}
}
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