Literature DB >> 18420711

The relative value of operon predictions.

Rutger W W Brouwer1, Oscar P Kuipers, Sacha A F T van Hijum.   

Abstract

For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation, (iv) sequence elements and (v) experimental evidence. The performance estimates of operon predictions reported in literature cannot directly be compared due to differences in methods and data used in these studies. Here, we survey the current status of operon prediction methods. Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement. We expect that existing and newly generated genomics and transcriptomics data will further improve accuracy of operon prediction methods.

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Year:  2008        PMID: 18420711     DOI: 10.1093/bib/bbn019

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  50 in total

Review 1.  Mechanisms and evolution of control logic in prokaryotic transcriptional regulation.

Authors:  Sacha A F T van Hijum; Marnix H Medema; Oscar P Kuipers
Journal:  Microbiol Mol Biol Rev       Date:  2009-09       Impact factor: 11.056

2.  Analysis of strand-specific RNA-seq data using machine learning reveals the structures of transcription units in Clostridium thermocellum.

Authors:  Wen-Chi Chou; Qin Ma; Shihui Yang; Sha Cao; Dawn M Klingeman; Steven D Brown; Ying Xu
Journal:  Nucleic Acids Res       Date:  2015-03-12       Impact factor: 16.971

3.  Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis.

Authors:  Brewster Hayles; Sailu Yellaboina; Degeng Wang
Journal:  PLoS One       Date:  2010-03-26       Impact factor: 3.240

4.  Identification of novel non-coding small RNAs from Streptococcus pneumoniae TIGR4 using high-resolution genome tiling arrays.

Authors:  Ranjit Kumar; Pratik Shah; Edwin Swiatlo; Shane C Burgess; Mark L Lawrence; Bindu Nanduri
Journal:  BMC Genomics       Date:  2010-06-03       Impact factor: 3.969

5.  Operon structure of Staphylococcus aureus.

Authors:  Nicole J P ten Broeke-Smits; Tessa E Pronk; Ilse Jongerius; Oskar Bruning; Floyd R Wittink; Timo M Breit; Jos A G van Strijp; Ad C Fluit; C H Edwin Boel
Journal:  Nucleic Acids Res       Date:  2010-02-11       Impact factor: 16.971

6.  High accuracy operon prediction method based on STRING database scores.

Authors:  Blanca Taboada; Cristina Verde; Enrique Merino
Journal:  Nucleic Acids Res       Date:  2010-04-12       Impact factor: 16.971

7.  Computational prediction of the osmoregulation network in Synechococcus sp. WH8102.

Authors:  Xizeng Mao; Victor Olman; Rhona Stuart; Ian T Paulsen; Brian Palenik; Ying Xu
Journal:  BMC Genomics       Date:  2010-05-10       Impact factor: 3.969

8.  Simultaneous prediction of transcription factor binding sites in a group of prokaryotic genomes.

Authors:  Shaoqiang Zhang; Shan Li; Phuc T Pham; Zhengchang Su
Journal:  BMC Bioinformatics       Date:  2010-07-23       Impact factor: 3.169

9.  Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

Authors:  Xiao Chang; Shuai Liu; Yong-Tao Yu; Yi-Xue Li; Yuan-Yuan Li
Journal:  PLoS One       Date:  2010-08-12       Impact factor: 3.240

10.  DOOR: a database for prokaryotic operons.

Authors:  Fenglou Mao; Phuongan Dam; Jacky Chou; Victor Olman; Ying Xu
Journal:  Nucleic Acids Res       Date:  2008-11-06       Impact factor: 16.971

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