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Features for computational operon prediction in prokaryotes
Authors:Chuang Li-Yeh  Chang Hsueh-Wei  Tsai Jui-Hung  Yang Cheng-Hong
Affiliation:Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Taiwan.
Abstract: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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