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Features for computational operon prediction in prokaryotes

Accurate prediction of operons can improve the functional annotation and application of genes within operons in prokaryotes. Here, we review several features: (i) intergenic distance, (ii) metabolic pathways, (iii) homologous genes, (iv) promoters and terminators, (v) gene order conservation, (vi) m...

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Published in:Briefings in functional genomics 2012-07, Vol.11 (4), p.291-299
Main Authors: Chuang, Li-Yeh, Chang, Hsueh-Wei, Tsai, Jui-Hung, Yang, Cheng-Hong
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description Accurate prediction of operons can improve the functional annotation and application of genes within operons in prokaryotes. Here, we review several features: (i) intergenic distance, (ii) metabolic pathways, (iii) homologous genes, (iv) promoters and terminators, (v) gene order conservation, (vi) microarray, (vii) clusters of orthologous groups, (viii) gene length ratio, (ix) phylogenetic profiles, (x) operon length/size and (xi) STRING database scores, as well as some other features, which have been applied in recent operon prediction methods in prokaryotes in the literature. Based on a comparison of the prediction performances of these features, we conclude that other, as yet undiscovered features, or feature selection with a receiver operating characteristic analysis before algorithm processing can improve operon prediction in prokaryotes.
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subjects Algorithms
Bacillus subtilis - genetics
Cluster Analysis
Computational Biology - methods
Databases, Genetic
Genome, Bacterial
Oligonucleotide Array Sequence Analysis
Operon
Phylogeny
Prokaryotic Cells - cytology
Promoter Regions, Genetic
Reproducibility of Results
ROC Curve
Sensitivity and Specificity
title Features for computational operon prediction in prokaryotes
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