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bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli
MOTIVATION: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the si...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408793/ https://www.ncbi.nlm.nih.gov/pubmed/27694198 http://dx.doi.org/10.1093/bioinformatics/btw629 |
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author | Shahmuradov, Ilham Ayub Mohamad Razali, Rozaimi Bougouffa, Salim Radovanovic, Aleksandar Bajic, Vladimir B |
author_facet | Shahmuradov, Ilham Ayub Mohamad Razali, Rozaimi Bougouffa, Salim Radovanovic, Aleksandar Bajic, Vladimir B |
author_sort | Shahmuradov, Ilham Ayub |
collection | PubMed |
description | MOTIVATION: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the sigma (σ) factor proteins, which control the gene activation. The majority of published bacterial promoter prediction tools target σ(70) promoters in Escherichia coli. Moreover, no σ-specific classification of promoters is available for prokaryotes other than for E. coli. RESULTS: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σ(A), σ(C), σ(H), σ(G) and σ(F)) and for five classes of sigma factors in E. coli (σ(70), σ(38), σ(32), σ(28) and σ(24)). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC = 0.86, F(1)-score = 0.93) compared to the next best tool with MCC = 0.59, F(1)-score = 0.79) and covers multiple classes of promoters. AVAILABILITY AND IMPLEMENTATION: bTSSfinder is available standalone and online at http://www.cbrc.kaust.edu.sa/btssfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5408793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54087932017-05-03 bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli Shahmuradov, Ilham Ayub Mohamad Razali, Rozaimi Bougouffa, Salim Radovanovic, Aleksandar Bajic, Vladimir B Bioinformatics Original Papers MOTIVATION: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the sigma (σ) factor proteins, which control the gene activation. The majority of published bacterial promoter prediction tools target σ(70) promoters in Escherichia coli. Moreover, no σ-specific classification of promoters is available for prokaryotes other than for E. coli. RESULTS: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σ(A), σ(C), σ(H), σ(G) and σ(F)) and for five classes of sigma factors in E. coli (σ(70), σ(38), σ(32), σ(28) and σ(24)). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC = 0.86, F(1)-score = 0.93) compared to the next best tool with MCC = 0.59, F(1)-score = 0.79) and covers multiple classes of promoters. AVAILABILITY AND IMPLEMENTATION: bTSSfinder is available standalone and online at http://www.cbrc.kaust.edu.sa/btssfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-02-01 2016-09-30 /pmc/articles/PMC5408793/ /pubmed/27694198 http://dx.doi.org/10.1093/bioinformatics/btw629 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Shahmuradov, Ilham Ayub Mohamad Razali, Rozaimi Bougouffa, Salim Radovanovic, Aleksandar Bajic, Vladimir B bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title | bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title_full | bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title_fullStr | bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title_full_unstemmed | bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title_short | bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli |
title_sort | btssfinder: a novel tool for the prediction of promoters in cyanobacteria and escherichia coli |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408793/ https://www.ncbi.nlm.nih.gov/pubmed/27694198 http://dx.doi.org/10.1093/bioinformatics/btw629 |
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