bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli

Handle URI:
http://hdl.handle.net/10754/622037
Title:
bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli
Authors:
Shahmuradov, Ilham; Mohamad Razali, Rozaimi ( 0000-0002-8996-3975 ) ; Bougouffa, Salim ( 0000-0001-9218-6452 ) ; Radovanovic, Aleksandar; Bajic, Vladimir B. ( 0000-0001-5435-4750 )
Abstract:
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 σ70 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 (σA, σC, σH, σG and σF) and for five classes of sigma factors in E. coli (σ70, σ38, σ32, σ28 and σ24). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC=0.86, F1-score=0.93) compared to the next best tool with MCC=0.59, F1-score=0.79) and covers multiple classes of promoters.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Shahmuradov IA, Mohamad Razali R, Bougouffa S, Radovanovic A, Bajic VB (2016) bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli. Bioinformatics: btw629. Available: http://dx.doi.org/10.1093/bioinformatics/btw629.
Publisher:
Oxford University Press (OUP)
Journal:
Bioinformatics
KAUST Grant Number:
URF/1/1976,02; FCS/1/2448,01
Issue Date:
29-Sep-2016
DOI:
10.1093/bioinformatics/btw629
Type:
Article
ISSN:
1367-4803; 1460-2059
Sponsors:
This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Awards No URF/1/1976,02 and FCS/1/2448,01.
Additional Links:
http://bioinformatics.oxfordjournals.org/content/early/2016/09/27/bioinformatics.btw629
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorShahmuradov, Ilhamen
dc.contributor.authorMohamad Razali, Rozaimien
dc.contributor.authorBougouffa, Salimen
dc.contributor.authorRadovanovic, Aleksandaren
dc.contributor.authorBajic, Vladimir B.en
dc.date.accessioned2016-12-20T05:52:11Z-
dc.date.available2016-12-20T05:52:11Z-
dc.date.issued2016-09-29en
dc.identifier.citationShahmuradov IA, Mohamad Razali R, Bougouffa S, Radovanovic A, Bajic VB (2016) bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli. Bioinformatics: btw629. Available: http://dx.doi.org/10.1093/bioinformatics/btw629.en
dc.identifier.issn1367-4803en
dc.identifier.issn1460-2059en
dc.identifier.doi10.1093/bioinformatics/btw629en
dc.identifier.urihttp://hdl.handle.net/10754/622037-
dc.description.abstractMotivation: 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 σ70 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 (σA, σC, σH, σG and σF) and for five classes of sigma factors in E. coli (σ70, σ38, σ32, σ28 and σ24). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC=0.86, F1-score=0.93) compared to the next best tool with MCC=0.59, F1-score=0.79) and covers multiple classes of promoters.en
dc.description.sponsorshipThis publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Awards No URF/1/1976,02 and FCS/1/2448,01.en
dc.publisherOxford University Press (OUP)en
dc.relation.urlhttp://bioinformatics.oxfordjournals.org/content/early/2016/09/27/bioinformatics.btw629en
dc.rightsThis 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.comen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.titlebTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia colien
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalBioinformaticsen
dc.eprint.versionPublisher's Version/PDFen
kaust.authorShahmuradov, Ilhamen
kaust.authorMohamad Razali, Rozaimien
kaust.authorBougouffa, Salimen
kaust.authorRadovanovic, Aleksandaren
kaust.authorBajic, Vladimir B.en
kaust.grant.numberURF/1/1976,02en
kaust.grant.numberFCS/1/2448,01en
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