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...

Full description

Saved in:
Bibliographic Details
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
Format: Article
Language:English
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
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2041-2649
2041-2657
DOI:10.1093/bfgp/els024