ArticleFrontiers in microbiology2022
Sigma70Pred: A highly accurate method for predicting sigma70 promoter in
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- External factors influence intrinsic differences in Stx2e production by Porcine Shiga Toxin-producing Escherichia coli strains.PLoS pathogens · 2025Article
- Bioinformatic exploration reveals features of tenpIN family of type III toxin-antitoxin systems in bacteria and viruses.Scientific reports · 2025Article
- iProL: identifying DNA promoters from sequence information based on Longformer pre-trained model.BMC bioinformatics · 2024Article
- Comprehensive Characterization ofInternational journal of molecular sciences · 2024Article
- Computational identification of promoters inFrontiers in microbiology · 2023Article
- Article
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5 authors.
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Abstract
Sigma70 factor plays a crucial role in prokaryotes and regulates the transcription of most of the housekeeping genes. One of the major challenges is to predict the sigma70 promoter or sigma70 factor binding site with high precision. In this study, we trained and evaluate our models on a dataset consists of 741 sigma70 promoters and 1,400 non-promoters. We have generated a wide range of features around 8,000, which includes Dinucleotide Auto-Correlation, Dinucleotide Cross-Correlation, Dinucleotide Auto Cross-Correlation, Moran Auto-Correlation, Normalized Moreau-Broto Auto-Correlation, Parallel Correlation Pseudo Tri-Nucleotide Composition, etc. Our SVM based model achieved maximum accuracy 97.38% with AUROC 0.99 on training dataset, using 200 most relevant features. In order to check the robustness of the model, we have tested our model on the independent dataset made by using RegulonDB10.8, which included 1,134 sigma70 and 638 non-promoters, and able to achieve accuracy of 90.41% with AUROC of 0.95. Our model successfully predicted constitutive promoters with accuracy of 81.46% on an independent dataset. We have developed a method, Sigma70Pred, which is available as webserver and standalone packages at https://webs.iiitd.edu.in/raghava/sigma70pred/. The services are freely accessible.
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