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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 |
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creator | Chuang, Li-Yeh Chang, Hsueh-Wei Tsai, Jui-Hung Yang, Cheng-Hong |
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. |
doi_str_mv | 10.1093/bfgp/els024 |
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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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