ArticlePeerJ. Computer science2021
Comparison of machine learning and deep learning techniques in promoter prediction across diverse species.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 44 citations in OpenAlex.
- Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches?Journal of virology · 2026Review
- Design prokaryotic cis-regulatory elements using language model.Nucleic acids research · 2026Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Synthetic promoter design in plants: integration of computational and experimental approaches.Frontiers in plant science · 2026Review
- Integrating yeast biodiversity and machine learning for predictive metabolic engineering.FEMS yeast research · 2025Review
- Navigating the Multiverse: a Hitchhiker's guide to selecting harmonization methods for multimodal biomedical data.Biology methods & protocols · 2025Review
- Genome language modeling (GLM): a beginner's cheat sheet.Biology methods & protocols · 2025Article
- Article
- A rapid and scalable approach to build synthetic repetitive hormone-responsive promoters.Plant biotechnology journal · 2024Article
- gRNA Design: How Its Evolution Impacted on CRISPR/Cas9 Systems Refinement.Biomolecules · 2023Review
- Designing artificial synthetic promoters for accurate, smart, and versatile gene expression in plants.Plant communications · 2023Review
- Deep learning and support vector machines for transcription start site identification.PeerJ. Computer science · 2023Article
- Nonlinear physics opens a new paradigm for accurate transcription start site prediction.BMC bioinformatics · 2022Article
- A comprehensive survey on computational learning methods for analysis of gene expression data.Frontiers in molecular biosciences · 2022Review
- TSSNote-CyaPromBERT: Development of an integrated platform for highly accurate promoter prediction and visualization ofFrontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene promoters are the key DNA regulatory elements positioned around the transcription start sites and are responsible for regulating gene transcription process. Various alignment-based, signal-based and content-based approaches are reported for the prediction of promoters. However, since all promoter sequences do not show explicit features, the prediction performance of these techniques is poor. Therefore, many machine learning and deep learning models have been proposed for promoter prediction. In this work, we studied methods for vector encoding and promoter classification using genome sequences of three distinct higher eukaryotes viz. yeast (Saccharomyces cerevisiae),
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Registered trials
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