ArticleAll life2023
QPromoters: sequence based prediction of promoter strength in
Article in All life, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Dissecting the causal polymorphism of the Lr67res multipathogen resistance gene.Journal of experimental botany · 2024Article
- Deep Learning-Assisted Design of Novel Promoters inAdvanced genetics (Hoboken, N.J.) · 2023Article
- Insight to Gene Expression From Promoter Libraries With the Machine Learning Workflow Exp2Ipynb.Frontiers in bioinformatics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Promoters play a key role in influencing transcriptional regulation for fine-tuning the expression of genes. Heterologous promoter engineering has been a widely used concept to control the level of transcription in all model organisms. The strength of a promoter is mainly determined by its nucleotide composition. Many promoter libraries have been curated, but few have attempted to develop theoretical methods to predict the strength of promoters from their nucleotide sequence. Such theoretical methods are not only valuable in the design of promoters with specified strength but are also meaningful in understanding the mechanistic role of promoters in transcriptional regulation. In this study, we present a theoretical model to describe the relationship between promoter strength and nucleotide sequence in
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.