SAPPHIRE: a neural network based classifier for σ70 promoter prediction in Pseudomonas

Background In silico promoter prediction represents an important challenge in bioinformatics as it provides a first-line approach to identifying regulatory elements to support wet-lab experiments. Historically, available promoter prediction software have focused on sigma factor-associated promoters...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 21; no. 1; pp. 1 - 7
Main Authors: Coppens, Lucas, Lavigne, Rob
Format: Journal Article
Language:English
Published: London BioMed Central 22.09.2020
Springer Nature B.V
BMC
Subjects:
Algorithms
Annotations
Artificial neural networks
Bias
Bioinformatics
Biomedical and Life Sciences
Biotechnology
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer programs
Datasets
E coli
Genera
Genomes
Infections
Life Sciences
Microarrays
Neural networks
Predictions
Programming languages
Promoters
Pseudomonas
Regulatory sequences
RNA polymerase
Sapphire
Sequence analysis
Sigma factor
Software
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary:Background In silico promoter prediction represents an important challenge in bioinformatics as it provides a first-line approach to identifying regulatory elements to support wet-lab experiments. Historically, available promoter prediction software have focused on sigma factor-associated promoters in the model organism E. coli. As a consequence, traditional promoter predictors yield suboptimal predictions when applied to other prokaryotic genera, such as Pseudomonas, a Gram-negative bacterium of crucial medical and biotechnological importance. Results We developed SAPPHIRE, a promoter predictor for σ70 promoters in Pseudomonas. This promoter prediction relies on an artificial neural network that evaluates sequences on their similarity to the − 35 and − 10 boxes of σ70 promoters found experimentally in P. aeruginosa and P. putida . SAPPHIRE currently outperforms established predictive software when classifying Pseudomonas σ70 promoters and was built to allow further expansion in the future. Conclusions SAPPHIRE is the first predictive tool for bacterial σ70 promoters in Pseudomonas . SAPPHIRE is free, publicly available and can be accessed online at www.biosapphire.com . Alternatively, users can download the tool as a Python 3 script for local application from this site.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-020-03730-z