Literature DB >> 12169564

Identifying operons and untranslated regions of transcripts using Escherichia coli RNA expression analysis.

Brian Tjaden1, David R Haynor, Sergey Stolyar, Carsten Rosenow, Eugene Kolker.   

Abstract

Microarrays traditionally have been used to assay the transcript expression of coding regions of genes. Here, we use Escherichia coli oligonucleotide microarrays to assay transcript expression of both open reading frames (ORFs) and intergenic regions. We then use hidden Markov models to analyse this expression data and estimate transcription boundaries of genes. This approach allows us to identify 5' untranslated regions (5' UTRs) of transcripts as well as genes that are likely to be operon members. The operon elements we identify correspond to documented operons with 99% specificity and 63% sensitivity. Similarly we find that our 5' UTR results accurately coincide with experimentally verified promoter regions for most genes.

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Year:  2002        PMID: 12169564     DOI: 10.1093/bioinformatics/18.suppl_1.s337

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  17 in total

1.  Global RNA half-life analysis in Escherichia coli reveals positional patterns of transcript degradation.

Authors:  Douglas W Selinger; Rini Mukherjee Saxena; Kevin J Cheung; George M Church; Carsten Rosenow
Journal:  Genome Res       Date:  2003-02       Impact factor: 9.043

2.  Improving the sensitivity and specificity of gene expression analysis in highly related organisms through the use of electronic masks.

Authors:  Shailender Nagpal; Mazen W Karaman; Michelle M Timmerman; Vincent V Ho; Brian L Pike; Joseph G Hacia
Journal:  Nucleic Acids Res       Date:  2004-03-18       Impact factor: 16.971

3.  Prediction of small, noncoding RNAs in bacteria using heterogeneous data.

Authors:  Brian Tjaden
Journal:  J Math Biol       Date:  2007-03-13       Impact factor: 2.259

Review 4.  A computational system for identifying operons based on RNA-seq data.

Authors:  Brian Tjaden
Journal:  Methods       Date:  2019-04-04       Impact factor: 3.608

5.  Initial proteome analysis of model microorganism Haemophilus influenzae strain Rd KW20.

Authors:  Eugene Kolker; Samuel Purvine; Michael Y Galperin; Serg Stolyar; David R Goodlett; Alexey I Nesvizhskii; Andrew Keller; Tao Xie; Jimmy K Eng; Eugene Yi; Leroy Hood; Alex F Picone; Tim Cherny; Brian C Tjaden; Andrew F Siegel; Thomas J Reilly; Kira S Makarova; Bernhard O Palsson; Arnold L Smith
Journal:  J Bacteriol       Date:  2003-08       Impact factor: 3.490

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.  Discovery and Characterization of Native Deinococcus radiodurans Promoters for Tunable Gene Expression.

Authors:  Angela Chen; Mark W Sherman; Cynthia Chu; Natalia Gonzalez; Tulshi Patel; Lydia M Contreras
Journal:  Appl Environ Microbiol       Date:  2019-10-16       Impact factor: 4.792

8.  Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae.

Authors:  Eugene Kolker; Kira S Makarova; Svetlana Shabalina; Alex F Picone; Samuel Purvine; Ted Holzman; Tim Cherny; David Armbruster; Robert S Munson; Grigory Kolesov; Dmitrij Frishman; Michael Y Galperin
Journal:  Nucleic Acids Res       Date:  2004-04-30       Impact factor: 16.971

9.  Tiling array analysis of UV treated Escherichia coli predicts novel differentially expressed small peptides.

Authors:  Gard O S Thomassen; Ragnhild Weel-Sneve; Alexander D Rowe; James A Booth; Jessica M Lindvall; Karin Lagesen; Knut I Kristiansen; Magnar Bjørås; Torbjørn Rognes
Journal:  PLoS One       Date:  2010-12-23       Impact factor: 3.240

10.  An approach for clustering gene expression data with error information.

Authors:  Brian Tjaden
Journal:  BMC Bioinformatics       Date:  2006-01-12       Impact factor: 3.169

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