ReviewMicroorganisms2021
Review in Microorganisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 22 citations in OpenAlex.
- High levels of antisense transcription from numerous genes in the obligate intracellular bacteriumJournal of bacteriology · 2026Article
- Small Regulatory RNAs in Prokaryotes: Key Features, Identification, Environmental Roles, and Applications.Microorganisms · 2026Review
- An antisense RNA regulates production of DnaA and affects sporulation in Bacillus subtilis.PLoS genetics · 2025Article
- Identification of Small RNAs inInternational journal of molecular sciences · 2024Article
- sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.BMC genomics · 2024Article
- Regulatory RNAs inSynthetic and systems biotechnology · 2024Review
- Genome-wide annotation of transcript boundaries using bacterial Rend-seq datasets.Microbial genomics · 2024Article
- The RNA chaperone Hfq has a multifaceted role inFrontiers in cellular and infection microbiology · 2024Article
- Benchmarking of five NGS mapping tools for the reference alignment of bacterial outer membrane vesicles-associated small RNAs.Frontiers in microbiology · 2024Article
- TargetRNA3: predicting prokaryotic RNA regulatory targets with machine learning.Genome biology · 2023Article
- Design of artificial small regulatorySynthetic and systems biotechnology · 2023Article
- Termination factor Rho mediates transcriptional reprogramming of Bacillus subtilis stationary phase.PLoS genetics · 2023Article
- Article
- Role of nickel-regulated small RNA in modulation ofWorld journal of clinical cases · 2022Review
- A Sporulation-Specific sRNA Bvs196 Contributing to the Developing Spore inMicroorganisms · 2022Article
- The Role ofAntibiotics (Basel, Switzerland) · 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
2 authors at 1 institution in 1 country.
Funding
Abstract
Small regulatory RNAs (sRNAs) that act by base-pairing are the most abundant posttranscriptional regulators in all three kingdoms of life. Over the past 20 years, a variety of approaches have been employed to discover chromosome-encoded sRNAs in a multitude of bacterial species. However, although largely improved bioinformatics tools are available to predict potential targets of base-pairing sRNAs, it is still challenging to confirm these targets experimentally and to elucidate the mechanisms as well as the physiological role of their sRNA-mediated regulation. Here, we provide an overview of currently known
Indexed as
Identifiers
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.