ArticleScientific reports2018
Image-based promoter prediction: a promoter prediction method based on evolutionarily generated patterns.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Computational Pipeline for Targeted Integration and Variable Payload Expression in Bacteriophage Engineering.ACS synthetic biology · 2025Article
- iProL: identifying DNA promoters from sequence information based on Longformer pre-trained model.BMC bioinformatics · 2024Article
- Classification of Promoter Sequences from Human Genome.International journal of molecular sciences · 2023Article
- ProkBERT family: genomic language models for microbiome applications.Frontiers in microbiology · 2023Article
- Deep learning and support vector machines for transcription start site identification.PeerJ. Computer science · 2023Article
- Database of Potential Promoter Sequences in theBiology · 2022Article
- Binding of the HSF-1 DNA-binding domain to multimeric C. elegans consensus HSEs is guided by cooperative interactions.Scientific reports · 2022Article
- Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.Briefings in bioinformatics · 2022Article
- Promotech: a general tool for bacterial promoter recognition.Genome biology · 2021Article
- TSSFinder-fast and accurate ab initio prediction of the core promoter in eukaryotic genomes.Briefings in bioinformatics · 2021Article
- Explainability in transformer models for functional genomics.Briefings in bioinformatics · 2021Article
- Article
- ncPro-ML: An integrated computational tool for identifying non-coding RNA promoters in multiple species.Computational and structural biotechnology journal · 2020Article
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Authors and funding
5 authors.
Funding
Abstract
Prediction of promoter regions is crucial for studying gene function and regulation. The well-accepted position weight matrix method for this purpose relies on predefined motifs, which would hinder application across different species. Here, we introduce image-based promoter prediction (IBPP) as a method that creates an "image" from training promoter sequences using an evolutionary approach and predicts promoters by matching with the "image". We used Escherichia coli σ70 promoter sequences to test the performance of IBPP and the combination of IBPP and a support vector machine algorithm (IBPP-SVM). The "images" generated with IBPP could effectively distinguish promoter from non-promoter sequences. Compared with IBPP, IBPP-SVM showed a substantial improvement in sensitivity. Furthermore, both methods showed good performance for sequences of up to 2,000 nt in length. The performances of IBPP and IBPP-SVM were largely affected by the threshold and dimension of vectors, respectively. The source code and documentation are freely available at https://github.com/hahatcdg/IBPP .
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