bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli
Mohamad Razali, Rozaimi
Bajic, Vladimir B.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/622037
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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.
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.
SponsorsThis 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.
PublisherOxford University Press (OUP)
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