ReviewRNA biology2015
An assessment of bacterial small RNA target prediction programs.
Review in RNA biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
47 citing papers in PubMed.
- sRNA-mediated crosstalk between cell wall stress and galactose metabolism in Staphylococcus aureus.Nucleic acids research · 2025Article
- GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions.BMC bioinformatics · 2025Article
- Article
- Transposon mutagenesis screen ineLife · 2024Article
- How to do RNA-RNA Interaction Prediction? A Use-Case Driven Handbook Using IntaRNA.Methods in molecular biology (Clifton, N.J.) · 2024Review
- TargetRNA3: predicting prokaryotic RNA regulatory targets with machine learning.Genome biology · 2023Article
- sInterBase: a comprehensive database of Escherichia coli sRNA-mRNA interactions.Bioinformatics (Oxford, England) · 2023Article
- Web Services for RNA-RNA Interaction Prediction.Methods in molecular biology (Clifton, N.J.) · 2023Review
- sRNA-controlled iron sparing response in Staphylococci.Nucleic acids research · 2022Article
- sRNARFTarget: a fast machine-learning-based approach for transcriptome-wide sRNA target prediction.RNA biology · 2022Article
- Prokaryotic Genome Annotation.Methods in molecular biology (Clifton, N.J.) · 2022Article
- The small RNA RsaF regulates the expression of secreted virulence factors in Staphylococcus aureus Newman.Journal of microbiology (Seoul, Korea) · 2021Article
- Transcriptome architecture and regulation at environmental transitions in flavobacteria: the case of an important fish pathogen.ISME communications · 2021Article
- Systematics for types and effects of RNA variations.RNA biology · 2021Article
- The Small RNAs PA2952.1 and PrrH as Regulators of Virulence, Motility, and Iron Metabolism in Pseudomonas aeruginosa.Applied and environmental microbiology · 2021Article
- An Integrated Database of Small RNAs and Their Interplay With Transcriptional Gene Regulatory Networks in Corynebacteria.Frontiers in microbiology · 2021Article
- Interplay between Regulatory RNAs and Signal Transduction Systems during Bacterial Infection.Genes · 2020Review
- Inference of Bacterial Small RNA Regulatory Networks and Integration with Transcription Factor-Driven Regulatory Networks.mSystems · 2020Article
- Plugging Small RNAs into the Network.mSystems · 2020Article
- An mRNA-mRNA Interaction Couples Expression of a Virulence Factor and Its Chaperone in Listeria monocytogenes.Cell reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most bacterial regulatory RNAs exert their function through base-pairing with target RNAs. Computational prediction of targets is a busy research field that offers biologists a variety of web sites and software. However, it is difficult for a non-expert to evaluate how reliable those programs are. Here, we provide a simple benchmark for bacterial sRNA target prediction based on trusted E. coli sRNA/target pairs. We use this benchmark to assess the most recent RNA target predictors as well as earlier programs for RNA-RNA hybrid prediction. Moreover, we consider how the definition of mRNA boundaries can impact overall predictions. Recent algorithms that exploit both conservation of targets and accessibility information offer improved accuracy over previous software. However, even with the best predictors, the number of true biological targets with low scores and non-targets with high scores remains puzzling.
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What OpenQuestion holds
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.